A method is disclosed. The method includes transmitting interaction history information comprising at least a plurality of addresses to a server computer, receiving a challenge summary from the server computer, the challenge summary associates each address of the plurality of addresses to a challenge rate from a range of challenge rates, and determining a challenge rate threshold based on the challenge summary. The method also includes interacting with a user utilizing at least an address, determining if the challenge rate associated with the address exceeds the challenge rate threshold, performing an authentication of the user if the challenge rate associated with the address does not exceed the challenge rate threshold; and initiating an authorization process of the interaction with the user.
Disclosed are a system, method, and computer program product for user network activity anomaly detection. The method includes generating a multilayer graph from network resource data, and generating an adjacency matrix associated with each layer of the multilayer graph to produce a plurality of adjacency matrices. The method further includes assigning a weight to each adjacency matrix to produce a plurality of weights, and generating a merged single layer graph by merging the plurality of layers based on a weighted sum of the plurality of adjacency matrices using the plurality of weights. The method further includes generating a set of anomaly scores by generating, for each node in the merged single layer graph, an anomaly score. The method further includes determining a set of anomalous users based on the set of anomaly scores, detecting fraudulent network activity based on the set of anomalous users, and executing a fraud mitigation process.
Described are a system, method, and computer program product for efficiently joining time-series data tables. The method includes loading a first table and a second table into a memory and generating a set of first key-value pairs based on a set of first time-series records and a set of second key-value pairs based on a set of second time-series records. The method also includes sorting the set of first key-value pairs and the set of second key-value pairs. The method further includes interleaving the set of first key-value pairs with the set of second key-value pairs and sequentially matching the sets of time-series records to form a joined table. The method further includes, in response to matching each respective second time-series record with the respective first time-series record, removing the respective second time-series record from the at least one memory.
A data owner can provide shares of a cryptographic key to N key servers. The N key servers can store the shares of a cryptographic key from the data owner such that T shares of the cryptographic key can be used to reconstruct the cryptographic key. A client computer can send a blinded query to T key servers of the N key severs, wherein the T key servers can encrypt a blinded query of a client computer using the share of the cryptographic key to determine a partial encryption. The client computer can receive T partial encryptions, assemble T partial encryptions to form an encrypted blinded query, and deblind the encrypted blinded query. The client computer can then use the encrypted query to perform a search on encrypted data of a remote database server using a searchable symmetric encryption scheme.
H04L 9/14 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité utilisant plusieurs clés ou algorithmes
H04L 9/30 - Clé publique, c. à d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret
Provided are systems, methods, and computer program products for dynamic peer group analysis for systematic changes in large scale data. Data associated with a plurality of entities is received and a relational graph is generated based on the data. A target entity is selected and a peer group for the target entity is determined based on the relational graph. An average and a standard deviation of the risk scores of the peer group are calculated and used to determine whether a systematic change in the behavior of the peer group has occurred. Whether a change in behavior of the target entity is a false anomaly or a true anomaly is determined based on whether a systematic change in the behavior of the peer group has occurred. An action is performed based on whether the change in behavior of the target entity is a false anomaly or a true anomaly.
An issuing authority (IA) may validate the identity of a user and issue a digital license to the user. IA may generate IA public-private key pair, and provide IA public key to the certification authority (CA). IA may sign the digital license with IA private key, and provision the signed digital license on the user device. IA may request CA to certify the digital license. CA may use IA public key to validate the digital license, and sign IA public key with CA private key, thereby generating a digital certificate associated with the issuing authority that is linked to the digital license. A relying party may use CA public key to validate the digital license. The relying party can retrieve the information from the digital license and trust that the retrieved information is legitimate.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
G06F 21/10 - Protection de programmes ou contenus distribués, p.ex. vente ou concession de licence de matériel soumis à droit de reproduction
G06F 21/33 - Authentification de l’utilisateur par certificats
A method is disclosed. The method includes receiving, from a resource provider computer, a token request message comprising a credential, after a user provides the credential to the resource provider computer. The method also includes transmitting, to the resource provider computer, a token response message comprising one or more supplemental data identifiers and one or more tokens associated with the one or more supplemental data identifiers. The one or more tokens are linked to the credential. Then, a user selects a supplemental data identifier. The method also comprises receiving, from the resource provider computer, an authorization request message comprising a token of the one or more tokens, the token linked to the selected supplemental data identifier, and a value, determining the credential using the token; and transmitting, to an authorizing entity computer, a modified authorization request message comprising the credential, the value, and the supplemental data identifier.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
8.
System, Method, and Computer Program Product for Efficiently Joining Time-Series Data Tables
Described are a system, method, and computer program product for efficiently joining time-series data tables. The method includes loading a first table and a second table into a memory and generating a set of first key-value pairs based on a set of first time-series records and a set of second key-value pairs based on a set of second time-series records. The method also includes sorting the set of first key-value pairs and the set of second key-value pairs. The method further includes interleaving the set of first key-value pairs with the set of second key-value pairs and sequentially matching the sets of time-series records to form a joined table. The method further includes, in response to matching each respective second time-series record with the respective first time-series record, removing the respective second time-series record from the at least one memory.
G06F 7/08 - Tri, c. à d. rangement des supports d'enregistrement dans un ordre de succession numérique ou autre, selon la classification d'au moins certaines informations portées sur les supports
G06F 16/2458 - Types spéciaux de requêtes, p.ex. requêtes statistiques, requêtes floues ou requêtes distribuées
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuées; Architectures de systèmes de bases de données distribuées à cet effet
Embodiments of the invention are directed to methods, apparatuses, computer readable media and systems for providing, along with a token, a token assurance level and data used to generate the token assurance level. At the time a token is issued, one or more Identification and Verification (ID&V) methods may be performed to ensure that the token is replacing a PAN that was legitimately used by a token requestor. A token assurance level may be assigned to a given token in light of the type of ID&V that is performed and the entity performing the ID&V. Different ID&Vs may result in different token assurance levels. An issuer may wish to know the level of assurance and the data used in generating the level of assurance associated with a token prior to authorizing a payment transaction that uses the token.
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/12 - Architectures de paiement spécialement adaptées aux systèmes de commerce électronique
G06Q 20/20 - Systèmes de réseaux présents sur les points de vente
A user may conduct a plurality of access requests with a plurality of resource provider computers. A processor server computer may determine whether resource provider computers store access data associated with the user in various ways, including detecting patterns in sets of a plurality of access requests conducted between the user and each of the plurality of resource provider computers. Upon detecting that access data has changed, the processor server computer may automatically send the updated access data to each of the identified resource provider computer.
A computer-implemented method includes: receiving an inquiry request message identifying a first payment transaction having a plurality of transaction parameters and a risk score, where the risk score is generated by a machine-learning model based on the plurality of transaction parameters; for each transaction parameter of the plurality of transaction parameters, perturbing a value of the transaction parameter and re-analyzing the first payment transaction with the machine-learning model to generate a perturbed risk score based on the perturbed transaction parameter; determining at least one impact parameter from the plurality of transaction parameters by comparing the perturbed risk scores generated for each of the plurality of transaction parameters; and generating an inquiry response message based on the at least one impact parameter.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
A method for conducting cryptocurrency transactions at an access device. The method includes initiating communication with an access device operated by a second user in a transaction between the first user and the second user, and then transmitting a request for transaction data to the access device. The method also includes receiving the transaction data comprising a transaction amount and a second cryptocurrency address from the access device from the access device, and signing, using a private cryptographic key, the first cryptocurrency address, the second cryptocurrency address, and the amount to create a signed cryptocurrency transaction. The method also includes transmitting the signed cryptocurrency transaction to a node of a blockchain network, and receiving a cryptocurrency transaction identifier from the node. The method also comprises generating a cryptogram using at least an access token on the mobile application and at least some of the transaction data.
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06Q 20/10 - Architectures de paiement spécialement adaptées aux systèmes de banque à domicile
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p.ex. une autorité de certification, un notaire ou un tiers de confiance
A method includes receiving, by a user device, an interaction request message for an interaction. The interaction request message comprises a requested amount from a resource provider computer. A secure element on the user device selects between an offline balance and an offline amount of program tokens stored in the secure element. The offline amount of program tokens can be selected. The secure element on the user device can deduct the requested amount from the offline amount of program tokens. The user device can complete the interaction with the resource provider computer.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/06 - Circuits privés de paiement, p.ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
G06Q 20/10 - Architectures de paiement spécialement adaptées aux systèmes de banque à domicile
14.
System, Method, and Computer Program Product for Monitoring and Improving Data Quality
Provided is a computer-implemented method for monitoring and improving data quality of transaction data that may include receiving transaction data associated with a plurality of payment transactions from an acquirer system. The transaction data may include a transaction record associated with each payment transaction of the plurality of payment transactions. Each transaction record may include a plurality of data fields. Each respective data field of the plurality of data fields may be categorized into a respective type of a plurality of types. A data quality score for each respective data field of the plurality of data fields may be determined based on the respective type of the respective data field. A system and computer program product are also provided.
G06F 16/215 - Amélioration de la qualité des données; Nettoyage des données, p.ex. déduplication, suppression des entrées non valides ou correction des erreurs typographiques
Provided are methods for determining a dominant account profile of an account. The method may include receiving transaction data associated with a plurality of payment transactions conducted within a predetermined time interval of activation of an account involved in the plurality of payment transactions, generating a dominant account profile classification model, determining a plurality of prediction scores for the account based on the dominant account profile classification model and the transaction data, where determining the plurality of prediction scores includes determining, for the user, a prediction score for each dominant account profile, where a prediction score includes a prediction of whether the user will conduct a threshold value of payment transactions using the account in one or more payment transaction categories of a plurality of payment transaction categories, and communicating data associated with the plurality of prediction scores. Systems and computer program products are also disclosed.
A computer-implemented method includes: receiving an inquiry request message identifying a first payment transaction having a plurality of transaction parameters and a risk score, where the risk score is generated by a machine-learning model based on the plurality of transaction parameters; for each transaction parameter of the plurality of transaction parameters, perturbing a value of the transaction parameter and re-analyzing the first payment transaction with the machine-learning model to generate a perturbed risk score based on the perturbed transaction parameter; determining at least one impact parameter from the plurality of transaction parameters by comparing the perturbed risk scores generated for each of the plurality of transaction parameters; and generating an inquiry response message based on the at least one impact parameter.
A method includes receiving, by a network computer from a resource provider computer, a settlement request associated with an installment plan and a total amount associated with a user account. The network computer transmits, to the resource provider computer, a settlement response associated with the installment plan and the total amount. The network computer configures an installment record, the installment record comprising a plurality of installment times. Based on occurrence of an installment time, of the plurality of installment times in the installment record, the network computer transmits, to an authorizing computer, installment data associated with the installment record to an authorizing computer, wherein the authorizing computer transmits an installment payment request to a user responsive to receiving the installment data from the network computer.
In some embodiments, a malware detection system includes an attack channel removal unit, a feature extraction unit coupled to the attack channel removal unit, and a graphical encoding unit coupled to the feature extraction unit and a malware detection unit. In some embodiments, based upon graphically-encoded component-based features and monotonic features extracted from attack-channel-free software output by the attack channel removal unit, the malware detection unit detects malware in software input into the malware detection system. In some embodiments, the monotonic features extracted from the attack-channel free software and the graphically-encoded component-based features are combined to generate a combination monotonic-component based feature vector. In some embodiments, the combination monotonic-component based feature vector is used to detect malware using the malware detection system.
A method is disclosed. The method includes receiving, by a token service computer, a request to obtain a token, and then obtaining the token. The method also includes receiving a request to activate the token, after the token is used to conduct a transaction.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
20.
PRIVACY PROTECTED CONSUMERS IDENTITY FOR CENTRALIZED P2P NETWORK SERVICES
A method of communicating a payment request from a first payment platform to a second payment platform is disclosed. The method may receive a payment request from a sending user on the first payment platform to a receiving user on the second payment platform where the payment request from the sending user is translated into a protected payment request. In response to the sending user being known, the protected payment request may be communicated to the second payment platform. An acceptance of the protected payment request from the second payment platform may be received. A transaction settlement request may be communicated to the first payment platform and the second payment platform.
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
A method includes a sender device operated by a sender receiving a receiver address associated with a receiver. The sender device prompts the sender to interact a card comprising a processor and a memory storing a sender public key and a sender private key of a sender public-private key pair associated with a blockchain network, the card held by the sender. The sender device transmits interaction data including the receiver address, a sender address of the sender, and a value to the card. The processor of the card retrieves the sender private key and signs the interaction data to produce signed interaction data. The sender device receives the signed interaction data and the sender public key. The sender device transmits the interaction data and the signed interaction data to the blockchain network. The blockchain network records the interaction data and the signed interaction data in a block of a blockchain.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
H04L 67/1097 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau pour le stockage distribué de données dans des réseaux, p.ex. dispositions de transport pour le système de fichiers réseau [NFS], réseaux de stockage [SAN] ou stockage en réseau [NAS]
A method includes transmitting an authorization request message with a credential or a token associated with a first user to an authorizing entity computer, and then receiving, from the authorizing entity computer, an authorization response message; and responsive to receiving the authorization response message. The method also includes transmitting the credential or the token to a vehicle. The first user is able to access the vehicle by presenting a user device that contains the credential or token to the vehicle.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
Provided are systems for conducting private set intersection (PSI) techniques with multiple parties using a data repository that include at least one processor to generate a data repository, receive, from a submission entity system associated with a submission entity, a private set intersection (PSI) data query that includes a match parameter for performing the PSI data query, transmit, to the submission entity system, a data classification encryption key, wherein the data classification encryption key is associated with a data field that corresponds to a match parameter data field of the match parameter, determine whether to authorize the PSI data query on the data repository, transmit, to the submission entity system, a data authorization encryption key based on determining to authorize the PSI data query on the data repository, and perform the PSI data query on the data repository. Methods and computer program products are also provided.
An application data exchange technique may include a communication device establishing a communication channel with an access device, receiving an access device profile of the access device, and emulating a virtual access device on the communication device based on the access device profile. The virtual access device executing on the communication device may issue a set of application commands to a transaction applet executing on the communication device, and receive a set of application data responses from the transaction applet in response to the set of application commands. The communication device, may then generate a data packet by concatenating application data contained in the set of application data responses, and transmitting the data packet to the access device via the communication channel.
H04W 4/80 - Services utilisant la communication de courte portée, p.ex. la communication en champ proche, l'identification par radiofréquence ou la communication à faible consommation d’énergie
H04W 76/10 - Gestion de la connexion Établissement de la connexion
Embodiments of the present invention are directed to methods and systems for managing a cryptocurrency payment network comprising one or more issuer nodes and one or more distributor nodes. Issuer nodes may be granted different rights from distributor nodes with respect to the issuance and distribution of digital currency within the cryptocurrency payment network. A management system server computer may generate unique node verification key pairs for each node in the cryptocurrency payment network, where the node verification key pairs may be used to identify and authenticate issuer nodes and distributor nodes.
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
G06Q 20/06 - Circuits privés de paiement, p.ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
27.
SYSTEM AND METHOD FOR DEVICE TRANSACTION AUTHORIZATION
A computer-implemented method includes registering a user device and an internet-of-things (IOT) device for use in a transaction-by-proxy service; collecting behavior-related data associated with a user of the user device and the first IOT device; and using the behavior-related data as part of the transaction-by-proxy service to generate a transaction-by-proxy at the IOT device on behalf of the user of the user device. The computer-implemented method further includes generating a transaction-by-proxy model using the behavior-related data associated with the user and training the transaction-by-proxy model to determine whether to request the transaction-by-proxy.
G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p.ex. une autorité de certification, un notaire ou un tiers de confiance
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/30 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques
28.
INTEGRATING IDENTITY TOKENS AND PRIVACY-PRESERVING IDENTITY ATTRIBUTE ATTESTATIONS INTO INTERACTIONS
A method is disclosed. The method comprises receiving, by an identity network computer, a query set including a plurality of test identity attributes. After receiving the query set, the identity network computer may retrieve derivatives of identity attributes associated with a user, and an encrypted trapdoor, then compute an obscured query set using the query set, and optionally the derivatives of identity attributes. The identity network computer may transmit the obscured query set (i) and the encrypted trapdoor to a user device associated with the user, which generates and transmits a first modified trapdoor and the obscured query set to a relying party computer, or (ii) and a second modified trapdoor to the relying party computer. The relying party computer may thereafter use the obscured query set, and the first modified trapdoor or the second modified trapdoor, to determine if the identity attributes is a member of the query set.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
H04L 9/30 - Clé publique, c. à d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret
An identity chaining fraud detection method that allows each current transaction to be linked to other transactions through commonly shared identities. Over a period of time the links create a chain of associated transactions which can be analyzed to determine if identity variances occur, which indicates that fraud is detected. Additionally, if a specific identity is detected as being fraudulent, that identity can be tagged as fraudulent and can be referenced by a plurality of other merchant transaction chains to determine fraud.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
30.
System, Method, and Computer Program Product for Efficiently Storing Multi-Threaded Log Data
Systems, methods, and computer program products are provided for efficiently storing multi-threaded log data. A method includes receiving multi-threaded log data comprising logs, markers, and thread identifiers. For each respective log, the respective thread identifier is set as a most recently used item in a thread reference cache. A respective log cache in a map data structure is determined based on the respective thread identifier. The respective log is added to the respective log cache. Whether to communicate the respective log and/or the respective log cache to a first repository is determined based on the respective marker. The respective log is communicated to a second repository. Whether to remove an oldest log from the log cache is determined based on a log cache size limit and/or a time limit. Whether to remove a least recently used log cache is determined based on at least one map data structure size limit.
A method, system, and computer program product is provided for embedding compression and reconstruction. The method includes receiving embedding vector data comprising a plurality of embedding vectors. A beta-variational autoencoder is trained based on the embedding vector data and a loss equation. The method includes determining a respective entropy of a respective mean and a respective variance of each respective dimension of a plurality of dimensions. A first subset of the plurality of dimensions is determined based on the respective entropy of the respective mean and the respective variance for each respective dimension of the plurality of dimensions. A second subset of the plurality of dimensions is discarded based on the respective entropy of the respective mean and the respective variance for each respective dimension of the plurality of dimensions. The method includes generating a compressed representation of the embedding vector data based on the first subset of dimensions.
Provided is a computer-implemented method, system, and computer program product for leasing decoupled configurations and managing configuration lease persistence with application state management including receiving a configuration set lease request from a client application in response to the client application being launched. In response to receiving the configuration set lease request, the method, system, and computer program product includes determining a unique configuration set from a pool of different configuration sets. Further, the method, system, and computer program product includes communicating the unique configuration set to the client application and activating a lease of the unique configuration set by associating the client application with the unique configuration set in a lease database. In response to determining that the lease is valid, persisting the lease in the lease database. In response to determining that the lease is invalid, deactivating the lease of the unique configuration set in the lease database.
A method includes a server computer receiving, from a first data provider computer, encrypted data derived from first identity data and a cryptographic key or derivative thereof stored at the first data provider computer. The server computer transmits, to a second data provider computer, the encrypted data and/or the cryptographic key or derivative thereof. The server computer receives, from the second data provider computer, intermediate data derived from second identity data stored at the second data provider computer. The server computer determines if the first identity data and the second identity data are duplicates while the first identity data and the second identity data are encrypted. The server computer removes one of encrypted first identity data, derived from the first identity data, and encrypted second identity data, derived from the second identity data, from a memory in the server computer.
A direct payment token generation method provides executable codes to a client device. The executable codes invokes functionalities in a browser application. The set of executable codes further provides login prompts to the user for logging to a virtual wallet account. The method provides a list of products for purchase from merchants in response to a successful login to the virtual wallet account. A graphical element is provided for purchasing one provided product from one of the merchants. In response to receiving a selection of the provided graphical element confirming the purchase, a payment token is generated for the virtual wallet account. The received selection includes confirming detailed information of the purchase. The payment token is transmitted to the client device and is embedded in a payment payload with the detailed information of the purchase. The payment load is transmitted to the one of the merchants to complete the purchase.
G06Q 20/12 - Architectures de paiement spécialement adaptées aux systèmes de commerce électronique
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
Embodiments relate to systems, apparatuses, and methods for performing transaction signing utilizing asymmetric cryptography and a private ledger. A transaction data is signed by a user device using a private key, and may be utilized in an authorization request message without including a real credential of the user. A transaction verification and accounting module (TVAM) can verify the signed transaction data and can continue processing the transaction.
G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p.ex. une autorité de certification, un notaire ou un tiers de confiance
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/34 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des cartes, p.ex. cartes à puces ou cartes magnétiques
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
G06Q 20/28 - Schémas de prépaiement, c. à d. de "paiement préalable"
G06Q 20/06 - Circuits privés de paiement, p.ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
36.
SYSTEM FOR DESIGNING AND VALIDATING FINE GRAINED FRAUD DETECTION RULES
A method includes receiving historical interaction data, which includes a plurality of historical interactions. Each historical interaction is associated with a plurality of data fields. The method includes assigning a plurality of weights to the plurality of data fields, generating a neural network using the plurality of weights and the plurality of data fields, identifying a first plurality of feature indicators indicative of a first class, the first class being different from a second class; receiving a second plurality of feature indicators derived from data relating to compromised accounts, updating, a probability distribution component using the first plurality of feature indicators and the second plurality of feature indicators, and receiving current data for an interaction. The method also includes applying the probability distribution component to the current data, and scoring the interaction using the probability distribution component.
G06F 18/213 - Extraction de caractéristiques, p.ex. en transformant l'espace des caractéristiques; Synthétisations; Mappages, p.ex. procédés de sous-espace
G06F 18/214 - Génération de motifs d'entraînement; Procédés de Bootstrapping, p.ex. ”bagging” ou ”boosting”
Abstract: Embodiments of the invention are directed to a user device. A fingerprint sensor can be located adjacent to electrical contacts. As a result, both the fingerprint sensor and the electrical contacts can be directly connected to an underlying memory within the user device. The direct connection allows the user device to be free of wires.
Provided are systems for generating a machine learning model and a prediction based on encoded time series data using model reduction techniques that include a processor to receive a training dataset of a plurality of data instances, wherein each data instance includes a time series of data points, perform an encoding operation on the training dataset to provide an encoded dataset having a lower dimension space than a dimension space of the training dataset, generate one or more prediction models based on the encoded dataset, determine an output of the one or more prediction models in the lower dimension space based on an input provided to the one or more prediction models, and perform a decoding operation on the output to project the output from the lower dimension space to the dimension space of the training dataset. Methods and computer program products are also provided.
The present disclosure discloses a method and a system for performing transaction. In an embodiment, when a user initiates a card transaction at an entity, the method comprises receiving card information of the user from the entity for performing transaction. In response to receiving the card information, the method comprises identifying whether an alternate identifier is present for the card information in a. first server. If the alternate identifier is present in the first server, the method comprises transmitting the alternate identifier from the first server and a cryptogram value associated with the alternate identifier to the entity for performing the transaction. If the alternate identifier is not present in the first server, the method comprises transmitting the alternate identifier for the card information by obtaining the alternate identifier from a second server and the cryptogram value associated with the alternate identifier to the entity for performing the transaction.
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p.ex. une autorité de certification, un notaire ou un tiers de confiance
G06Q 20/34 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des cartes, p.ex. cartes à puces ou cartes magnétiques
G06Q 20/14 - Architectures de paiement spécialement adaptées aux systèmes de facturation
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
40.
METHOD, SYSTEM, AND COMPUTER PROGRAM PRODUCT FOR GENERATING ROBUST GRAPH NEURAL NETWORKS USING UNIVERSAL ADVERSARIAL TRAINING
Described are a method, system, and computer program product for generating robust graph neural networks using universal adversarial training. The method includes receiving a graph neural network (GNN) model and a bipartite graph including an adjacency matrix, initializing model parameters of the GNN model, initializing perturbation parameters, and sampling a subgraph of a complementary graph based on the bipartite graph. The method further includes repeating until convergence of the model parameters: drawing a random variable from a uniform distribution; generating a universal perturbation matrix based on the subgraph, the random variable, and the perturbation parameters; determining Bayesian Personalized Ranking (BPR) loss by inputting the bipartite graph and the universal perturbation matrix to the GNN model; updating the perturbation parameters based on stochastic gradient ascent; and updating the model parameters based on stochastic gradient descent. The method further includes, in response to convergence of the model parameters, outputting the model parameters.
Systems, apparatuses, and methods are provided for enabling a transaction using a token associated with a first payment network to be conducted using a second payment network. When a transaction using a token is submitted to a payment network, the payment network can determine the payment network associated with the token. If the token is associated with a second payment network, a token verification request including the token can be sent to the second payment network. The second payment network can then return a token verification response including a primary account identifier such as a primary account number (PAN) corresponding to the token and a validation result. The transaction may then be processed using the primary account identifier.
A requestor and a responder may conduct secure communication by making API calls based on a secure multi-party protocol. The requestor may send a request data packet sent in a API request to the responder, where the request data packet can include at least a control block that is asymmetrically encrypted and a data block that is symmetrically encrypted. The responder may return a response data packet to the requestor, where the response data packet can include at least a control block and a data block that are both symmetrically encrypted. The requestor and the responder may derive the keys for decrypting the encrypted portions of the request and response data packets based on some information only known to the requestor and the responder. The secure multi-party protocol forgoes the need to store and manage keys in a hardware security module.
Systems, methods, and computer program products may store, in a distributed cache, a rule associated with a plurality of accounts in a Real-Time Payments (RTP) network, the rule being stored in association with account data associated with the plurality of accounts; receive an account level exclusion directive associated with the account; store, in the distributed cache, the account level exclusion directive in association with the account; receive transaction data associated with a transaction in the RTP network between the account and another account; retrieve, from the distributed cache, the rule, the account level exclusion directive, and the account data associated with the account; exclude, based on the account level exclusion directive, use of the rule for processing the transaction; and process, without applying the rule, the transaction in the RTP network.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/10 - Architectures de paiement spécialement adaptées aux systèmes de banque à domicile
44.
SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT FOR SECURE DATA DISTRIBUTION
A method, system, and computer program product is provided for secure data distribution. The system includes at least one processor programmed or configured to receive, from a first system, a data capture request, generate a data capture object including a plurality of orchestration rules and a first public key, digitally sign the data capture object with a second private key corresponding to a second public key, transmit the data capture object to the first system, receive encrypted user data including user data encrypted with the first public key, generate a transient token based on the user data and the plurality of orchestration rules, and distribute the transient token to each party of the plurality of parties by transmitting the transient token to the first system via a device.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
45.
PRIVACY-PRESERVING BIOMETRICS FOR MULTI-FACTOR AUTHENTICATION
A method includes generating a second public key and a second private key of a second public-private key pair, and transmitting the second public key to a first user device, which stores an encrypted biometric template. The encrypted biometric template is a biometric template encrypted with a first public key of a first public-private key pair. The first user device encrypts the encrypted biometric template with the second public key to form a double encrypted biometric template. The method includes receiving the double encrypted biometric template from the first user device, decrypting the double encrypted biometric template using the second private key to obtain the encrypted biometric template, determining a test biometric template and encrypting the test biometric template, comparing the encrypted test biometric template and the encrypted biometric template to obtain an encrypted biometric match score, and transmitting the encrypted biometric match score to a server computer.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
A method is disclosed and includes executing an integrated application comprising an SDK (software development kit) on a user device with a processor. The method includes determining, by the SDK and the processor on the user device, an checksum for the integrated application, validating, by the SDK in the user device, the integrated application using the determined checksum, and responsive to validating the determined checksum, performing, by the integrated application on the user device, an action.
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
41 - Éducation, divertissements, activités sportives et culturelles
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computer software, hardware, and firmware for creating, managing, and exchanging digital collectibles in the nature of downloadable virtual images, videos, and multimedia files authenticated by non-fungible tokens (NFTs) including relating to sports and sporting events in the real world and in virtual worlds including the metaverse; computer software in the field of digital currency, cryptocurrency, blockchain technology and non-fungible tokens (NFTs); computer software for users to view, access, store, monitor, manage, trade, send, receive, transmit, and exchange digital currency, virtual currency, cryptocurrency, digital and blockchain assets, and non-fungible tokens (NFTs); computer software for users to view, access, store, monitor, manage, trade, send, receive, transmit, and process virtual payments, including banking payments, payments by credit card, debit card, virtual payment card, including in virtual environments and virtual worlds including the metaverse; computer software for management and/or processing of digital transactions; computer software for use as a digital currency wallet and storage of non-fungible tokens; computer software for use as a cryptocurrency wallet; computer software used in auditing digital currency, virtual currency, cryptocurrency, digital and blockchain assets, digitized assets, digital tokens, crypto tokens and utility tokens; computer software for managing and verifying digital transactions, including cryptocurrency transactions using blockchain technology. Providing financial services in virtual environments and virtual worlds including the metaverse; providing virtual currency transaction processing services for others; cryptocurrency payment processing services; cryptocurrency exchange services featuring blockchain technology; issuance and redemption of tokens of value; virtual currency services; virtual currency exchange services; financial trading services in the field of nonfungible tokens, including financial exchange of virtual currency, in the field of nonfungible tokens (NFTs); electronic transfer of virtual currencies; financial sponsorship of sporting competitions, events, activities, and games in virtual worlds including the metaverse; financial services, namely providing a digital wallet that stores customer account information and enables them to make point-of-sales transactions, access coupons, vouchers, voucher codes and rebates at retailers and to obtain loyalty or monetary rewards that can be credited to their accounts via a cash-back system; financial services, namely providing a digital currency wallet; monetary and financial services in the nature of blockchain-based payment verification services; information, advisory and consultancy services relating to all the aforesaid services. Entertainment services, namely, providing on-line, non-downloadable virtual images, videos, and multimedia files relating to sports and sporting events in the real world and in virtual worlds including the metaverse, for use in virtual environments created for entertainment purposes authenticated by non-fungible tokens (NFTs); entertainment services, namely, providing online virtual environments in which users can interact for recreational, leisure or entertainment purposes accessible in virtual worlds including the metaverse. Providing online non-downloadable software in the field of digital currency, cryptocurrency, blockchain technology and non-fungible tokens (NFTs); providing temporary use of non-downloadable computer software for users to view, access, store, monitor, manage, trade, send, receive, transmit, and exchange digital currency, virtual currency, cryptocurrency, digital and blockchain assets, and non-fungible tokens (NFTs); providing online non-downloadable computer software for users to view, access, store, monitor, manage, trade, send, receive, transmit, and process virtual payments, including banking payments, payments by credit card, debit card, virtual payment card, including in virtual environments and virtual worlds including the metaverse; providing online non-downloadable computer software for management and/or processing of digital transactions; providing online non-downloadable computer software for use as a digital currency wallet and storage of non-fungible tokens; providing online non-downloadable computer software for use as a cryptocurrency wallet; providing online non-downloadable computer software used in auditing digital currency, virtual currency, cryptocurrency, digital and blockchain assets, digitized assets, digital tokens, crypto tokens and utility tokens; providing online non-downloadable computer software for managing and verifying digital transactions, including cryptocurrency transactions using blockchain technology; providing user authentication services using blockchain technology for transactions involving digital currency, virtual currency, cryptocurrency, digital and blockchain assets, and non-fungible tokens (NFTs); information, advisory and consultancy services relating to all the aforesaid services.
Methods and systems for managing cryptographic keys in on-premises and cloud computing environments and performing multi-party cryptography are disclosed. A cryptographic key can be retrieved from a hardware security module by a key management computer. The key management computer can generate key shares from the cryptographic key, and securely distribute the key shares to computer nodes or key share databases. The computer nodes can use the key shares in order to perform secure multi-party cryptography.
Described herein are systems and techniques for privacy-preserving unsupervised learning. The disclosed system and methods can enable separate computers, operated by separate entities, to perform unsupervised learning jointly based on a pool of their respective data, while preserving privacy. The system improves efficiency and scalability, while preserving privacy and avoids leaking a cluster identification. The system can jointly compute a secure distance via privacy-preserving multiplication of respective data values x and y from the computers based on a 1-out-of-N oblivious transfer (OT). In various embodiments, N may be 2, 4, or some other number of shares. A first computer can express its data value x in base-N. A second computer can form an ×N matrix comprising random numbers mi,0 and the remaining elements mi,j=(yjNi−mi,0) mod . The first computer can receive an output vector from the OT, having components mi=(yxi Ni−mi,0) mod .
A method comprises a security evaluation computer receiving access data from a user device of a user during an access request. The security evaluation computer analyzes the access data using authentication rules that each specify one of a plurality of authentication protocols for authenticating the user or the user device. At least one of the authentication rules specifies a security level flag for when no authentication is to be performed. The security evaluation computer triggers a first authentication rule corresponding to a first authentication protocol of the plurality of authentication protocols and implements the first authentication protocol. The security evaluation computer sends an authorization request message to an authorization server in a manner consistent with the first authentication protocol and then receive an authorization response message. The security evaluation computer analyzes, using authorization rules, the access data and the authorization response message to determine whether to complete the access request.
Described are a system, method, and computer program product for secure edge computing of a machine learning model. The method includes transmitting, with a server, a first portion of a machine learning model to a computing device remote from the server. The first portion includes at least one first layer of the machine learning model configured to process a first input of data collected by the computing device and generate an output. The method also includes receiving, with the server from the computing device, encoded model data including the output. The method further includes decoding, with the server, the encoded model data to produce decoded model data, and generating, with the server, a classification based on the first input of data by executing a second portion of the machine learning model.
G06F 18/241 - Techniques de classification relatives au modèle de classification, p.ex. approches paramétriques ou non paramétriques
G06F 9/50 - Allocation de ressources, p.ex. de l'unité centrale de traitement [UCT]
G06F 16/90 - Recherche d’informations; Structures de bases de données à cet effet; Structures de systèmes de fichiers à cet effet - Détails des fonctions des bases de données indépendantes des types de données cherchés
A computer-implemented method includes: receiving an inquiry request message identifying a first payment transaction having a first plurality of transaction parameters and a first authorization decision; querying a database including transaction data associated with a plurality of historical payment transactions to identify a subset of historical payment transactions, the transaction data including, for each of the plurality of historical payment transactions, a plurality of transaction parameters and an authorization decision, the subset of historical payment transactions including payment transactions having an authorization decision different from the first authorization decision and having a similarity score that satisfies a threshold; determining an impact parameter of the first plurality of transaction parameters by comparing the first plurality of transaction parameters with the plurality of transaction parameters associated with the plurality of historical payment transactions in the subset; and generating an inquiry response message based on the impact parameter.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06Q 10/0635 - Analyse des risques liés aux activités d’entreprises ou d’organisations
Systems, methods, and computer program products train a residual neural network including a first fully connected layer, a first recurrent neural network layer, and at least one skip connection for anomaly detection. The at least one skip connection directly connects at least one of (i) an output of the first fully connected layer to a first other layer downstream of the first recurrent neural network layer in the residual neural network and (ii) an output of the first recurrent neural network layer to a second other layer downstream of a second recurrent neural network layer in the residual neural network.
A method for verifying that event can take place before the event is executed is disclosed. A verification system is incorporated into an event processing network, such that the verification system can identify newly proposed events and determine whether they can be completed. The verification system can inform the network about verification results through distributed blockchain records. Other changes in event status can also be communicated through and stored in blockchain records.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
H04L 9/30 - Clé publique, c. à d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret
55.
System, Method, and Computer Program Product for Diagnosing Faulty Components in Networked Computer Systems
Described are a system, method, and computer program product for diagnosing faulty components in networked computer systems. The method includes receiving a plurality of alerts associated with a fault in a networked computer system. The method also includes generating a graph of a network topology of the networked computer system. The method further includes associating each alert with a node of the graph to determine a set of nodes affected by the fault. The method further includes determining a common node of the graph having a plurality of edges connected to nodes affected by the fault. The method further includes determining a faulty component based on the common node, retrieving a set of records of operational changes to the networked computer system, and determining, based on the set of records and the faulty component, an operational change that caused the fault in the networked computer system.
H04L 41/0631 - Gestion des fautes, des événements, des alarmes ou des notifications en utilisant l’analyse de la corrélation entre les notifications, les alarmes ou les événements en fonction de critères de décision, p.ex. la hiérarchie ou l’analyse temporelle ou arborescente
H04L 41/0659 - Gestion des fautes, des événements, des alarmes ou des notifications en utilisant la reprise sur incident de réseau en isolant ou en reconfigurant les entités défectueuses
H04L 41/12 - Découverte ou gestion des topologies de réseau
56.
Method, System, and Computer Program Product for Determining Solvency of a Digital Asset Exchange
Disclosed is a method, system, and computer program product for determining solvency of a digital asset exchange system. The method includes identifying a plurality of blockchain addresses corresponding to a plurality of users of a digital asset exchange system, generating a first commitment to an amount of digital assets corresponding to the plurality of blockchain addresses, and generating a second commitment to a balance of each user of the plurality of users. The method also includes generating a first component of a zero-knowledge algorithm that is configured to receive, as input, the first commitment. The method further includes generating, with at least one processor, a second component of the zero-knowledge algorithm that is configured to receive, as input, the second commitment. The method further includes determining that the digital asset exchange system is solvent based on the zero-knowledge algorithm.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/06 - Circuits privés de paiement, p.ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
H04L 9/06 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p.ex. système DES
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
A method for efficiently storing and verifying records is disclosed. The method may comprise receiving a first hash of first interaction data and determining an interaction identifier associated with the first hash, then storing the first hash in a database along with the interaction identifier and determining a root hash of a hash tree. In addition, the method may also comprise providing the root hash of the hash tree to a public blockchain. Embodiments of the invention also allow users to easily present records to a third party or inquiring entity. Furthermore, interactions may be processed more quickly than previous blockchain methods that publish to a block during each individual interaction.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
58.
Systems And Methods For Protecting Against Relay Attacks
Systems, methods, and devices are disclosed for preventing relay attacks. A user device may receive (e.g., when proximate to the first access device), from an intervening device, device identification data for a first access device. A message may be received from a second access device via the intervening device. The message may include a digital signature generated based at least in part on second access device identification data. The user device may validate the message utilizing the digital signature and a public key. If the message is invalid, the user device may discard the message. If the message is valid, (e.g., unaltered), the user device may determine that the user has not confirmed an intent to interact with the second access device and may terminate an further interaction with the second access device accordingly.
H04W 4/80 - Services utilisant la communication de courte portée, p.ex. la communication en champ proche, l'identification par radiofréquence ou la communication à faible consommation d’énergie
G07F 15/00 - Appareils déclenchés par pièces de monnaie avec distribution de liquide, de gaz ou d'électricité commandée par le comptage
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
An application or device is authenticated using secure application data validation. A server computer receives an authentication request comprising an application identifier or a user device identifier associated with a user device, the authentication request originating from the user device. The server computer receives a set of behavioral data associated with the application or the user device. Responsive to receiving the application identifier or device identifier, the server computer obtains a fuzzy vault associated with the application identifier or the user device identifier. The server computer determines a reconstructed key value using the fuzzy vault and the set of behavioral data. The application or the user device is authenticated using the reconstructed key value.
H04L 9/30 - Clé publique, c. à d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret
60.
SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT FOR ENERGY EFFICIENT GENERATION OF ARTIFICIAL NOISE TO PREVENT SIDE-CHANNEL ATTACKS
Methods, systems, and computer program products are provided for energy efficient generation of artificial noise to prevent side-channel attacks. An example method includes storing at least one secret value including secret value bits. At least one cryptographic operation is executed based on the at least one secret value. An artificial sequence generator stores at least one state indication based on a plurality of previous cryptographic operations executed on the device. A plurality of samples of artificial noise are generated, and a number of the plurality of samples is based on at least one power constraint parameter. Each sample of artificial noise of the plurality of samples of artificial noise is overlaid over a respective portion of a side channel signal based on the at least one state indication to mask leakage information associated with the at least one secret value on the side channel signal.
G06F 21/55 - Détection d’intrusion locale ou mise en œuvre de contre-mesures
G06F 7/72 - Méthodes ou dispositions pour effectuer des calculs en utilisant une représentation numérique non codée, c. à d. une représentation de nombres sans base; Dispositifs de calcul utilisant une combinaison de représentations de nombres codées et non codées utilisant l'arithmétique des résidus
G06F 9/44 - Dispositions pour exécuter des programmes spécifiques
G06F 21/00 - Dispositions de sécurité pour protéger les calculateurs, leurs composants, les programmes ou les données contre une activité non autorisée
H04L 9/00 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité
61.
SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT FOR DYNAMIC NODE CLASSIFICATION IN TEMPORAL-BASED MACHINE LEARNING CLASSIFICATION MODELS
Described are a system, method, and computer program product for dynamic node classification in temporal-based machine learning classification models. The method includes receiving graph data of a discrete time dynamic graph including graph snapshots, and node classifications associated with all nodes in the discrete time dynamic graph. The method includes converting the discrete time dynamic graph to a time-augmented spatio-temporal graph and generating an adjacency matrix based on a temporal walk of the time-augmented spatio-temporal graph. The method includes generating an adaptive information transition matrix based on the adjacency matrix and determining feature vectors based on the nodes and the node attribute matrix of each graph snapshot. The method includes generating and propagating initial node representations across information propagation layers using the adaptive information transition matrix and classifying a node of the discrete time dynamic graph subsequent to the first time period based on final node representations.
G06F 18/2323 - Techniques non hiérarchiques basées sur la théorie des graphes, p.ex. les arbres couvrants de poids minimal [MST] ou les coupes de graphes
G06F 16/90 - Recherche d’informations; Structures de bases de données à cet effet; Structures de systèmes de fichiers à cet effet - Détails des fonctions des bases de données indépendantes des types de données cherchés
G06F 18/241 - Techniques de classification relatives au modèle de classification, p.ex. approches paramétriques ou non paramétriques
A method performed by an access server is disclosed. The method including receiving a first access request including various fields of data for accessing a resource. The method may then generate a first fingerprint using a first value of a first field of the first access request and store the first fingerprint. After, the access server may receive a second access request, and generate a second fingerprint using a second value of the first field of the second access request. Then the first fingerprint can be compared to the second fingerprint to determine a possible match of the second access request to the first access request. A database is accessed using data of the first or second access request, to retrieve missing data in the first or second access request. The missing data can be compared to a corresponding field of the other access request to confirm a match.
A system, method, and computer program product is provided for secured, encrypted transaction processing. The method includes receiving a transaction request including a first user token including a first account balance, a second user token including a second account balance, and a transaction value. The method also includes generating a new first account balance by executing a zero-knowledge subtraction, and a new first user token including the new first account balance. The method further includes generating a new second account balance by executing a zero-knowledge addition, and a new second user token including the new second account balance. The method further includes transmitting the new tokens to the respective computing devices. The method further includes receiving a new transaction request including the new first user token and/or the new second user token, and generating a new account balance by executing a zero-knowledge computation based on the new transaction request.
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
H04L 9/30 - Clé publique, c. à d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06Q 40/02 - Opérations bancaires, p.ex. calcul d'intérêts ou tenue de compte
G06Q 20/10 - Architectures de paiement spécialement adaptées aux systèmes de banque à domicile
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
41 - Éducation, divertissements, activités sportives et culturelles
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
(1) Computer software, hardware, and firmware for creating, managing, and exchanging digital collectibles (1) Providing virtual currency transaction processing services for others; cryptocurrency payment processing services; cryptocurrency exchange services featuring blockchain technology; issuance of tokens of value; financial exchange of virtual currency, in the field of nonfungible tokens (NFTs); financial sponsorship of sporting competitions, events, activities, and games in the virtual world; financial services, providing a digital wallet that stores customer account information and enables them to make point-of-sales transactions, access coupons, vouchers, voucher codes and rebates at retailers and to obtain loyalty or monetary rewards that can be credited to their accounts via a cash-back system; financial services, providing a digital currency wallet; monetary and financial services in the nature of blockchain-based payment verification services
(2) Entertainment services, namely, providing on-line, non-downloadable virtual images, videos, and multimedia files for use in virtual environments authenticated by non-fungible tokens (NFTs); entertainment services, namely, providing online virtual environments in which users can interact for recreational, leisure or entertainment purposes accessible in the virtual world
(3) Providing temporary use of non-downloadable computer software for users to view, access, store, monitor, manage, trade, send, receive, transmit, and exchange digital currency, virtual currency, cryptocurrency, digital and blockchain assets, and non-fungible tokens (NFTs); providing online non-downloadable software for management of digital transactions; providing online non-downloadable software for use as a digital currency wallet and storage of non-fungible tokens; providing online non-downloadable software for use as a cryptocurrency wallet; providing online non-downloadable software used in auditing digital currency, virtual currency, cryptocurrency, digital and blockchain assets, digitized assets, digital tokens, crypto tokens and utility tokens; providing online non-downloadable computer software for managing and verifying cryptocurrency transactions using blockchain technology
65.
SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT FOR TIME-BASED ENSEMBLE LEARNING USING SUPERVISED AND UNSUPERVISED MACHINE LEARNING MODELS
Provided are systems for ensemble learning with machine learning models that include a processor to receive a training dataset of a plurality of data instances, wherein each data instance comprises a time series of data points, add an amount of time delay to one or more data instances to provide an augmented training dataset, select a first plurality of supervised machine learning models, select a second plurality of unsupervised machine learning models, train the first plurality of supervised machine learning models and the second plurality of unsupervised machine learning models based on the augmented training dataset, generate an ensemble machine learning model based on outputs of the supervised machine learning models and unsupervised machine learning models, and generate a runtime output of the ensemble machine learning model based on a runtime input to the ensemble machine learning model. Methods and computer program products are also provided.
Methods for authenticating digital transactions include receiving a device registration request, a device attestation response including a first token, and a selection of an authentication mode from a device. In response to receiving the device registration request and determining that the selected authentication mode is a static personal identification number (PIN) authentication mode, a device registration response is provided to the device. A first payment transaction request and an enrolment request to authenticate a second payment transaction request using the static PIN authentication mode are subsequently received from the device. The device is communicated with to receive the static PIN from the device. The device is enrolled based on the static PIN. Systems and computer program products are also provided.
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06Q 30/06 - Transactions d’achat, de vente ou de crédit-bail
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
67.
Computer-Implemented Method, System, and Computer Program Product for Automated Forecasting
A computer-implemented method for automated forecasting of cash flow includes: monitoring, while a plurality of first transactions are being processed in a payment network, payable transaction data associated with the plurality of first transactions, the plurality of first transactions initiated with at least one account issued to a merchant; monitoring, while a plurality of second transactions are being processed in a payment network, receivable transaction data associated with the plurality of second transactions, the plurality of second transactions between the merchant and a plurality of users; determining, based on the payable transaction data and the receivable transaction data, a plurality of seasonal variables; and generating a cash flow forecast associated with the merchant, the cash flow forecast generated based on the plurality of seasonal variables. A system and computer program product for automated forecasting of cash flow are also disclosed.
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
A method is disclosed. The method includes: a) receiving node identifiers from nodes of a plurality of nodes in a computer network; b) determining a plurality of node committees in a sampler graph comprising a plurality of nodes, wherein the node is present in a node committee in the plurality of node committees; c) and i) generating a random string; ii) performing a proof of work process using the random string and a hash function; iii) if the proof of work process yields a solution that is acceptable, then broadcasting the solution to all other nodes in the plurality of nodes, wherein the other nodes verify the solution; and iv) if the other nodes verify the solution, the node is elected to a subcommittee for the node committee, wherein the subcommittee updates the sampler graph; and d) repeating steps b) and c) until a leader committee is determined.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
H04L 12/18 - Dispositions pour la fourniture de services particuliers aux abonnés pour la diffusion ou les conférences
H04L 41/0893 - Affectation de groupes logiques aux éléments de réseau
G06Q 20/06 - Circuits privés de paiement, p.ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
Embodiments are directed to a method for determining an interview script in a claims submission. The method may comprising receiving data relating to a claim being submitted, which may include claims submission data input by a user, information relating to the user, and one or more features. Data associated with the one or more features may be determined from an artificial intelligence model. A first score based on the data associated with the one or more features and data associated with the information relating to the user may be determined and used to determine an interview script. In one embodiment, questions in the interview script may continue to be provided to the interviewer computer if a continually updated score remains above a predetermined threshold. In another embodiment, the user may be routed to a live interview with a human representative if a continually updated score drops below a predetermined threshold.
G06Q 30/016 - Fourniture d’une assistance aux clients, p. ex pour assister un client dans un lieu commercial ou par un service d’assistance après-vente
A method performs efficient data searches in a distributed computing system. The method may include, receiving a first key. The method may further include determining a hash map associated with the first key from among a plurality of hash maps. In some examples, the obtained hash map maps a partition of a set of keys to particular index values. The method may further include determining an index value associated with a second key using the determined hash map. The method may further include determining transaction processing data associated with the first key using the determined index value and providing the transaction processing data. Utilization of the plurality of hash maps may enable a data search to be performed using on-board memory of an electronic device of the distributed computing system.
G06F 16/22 - Indexation; Structures de données à cet effet; Structures de stockage
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuées; Architectures de systèmes de bases de données distribuées à cet effet
G06F 16/00 - Recherche d’informations; Structures de bases de données à cet effet; Structures de systèmes de fichiers à cet effet
A method is disclosed, and includes receiving from a token requestor, a token data request message comprising an initial resource provider identifier, and determining a permanent resource provider identifier using the initial resource provider identifier. The method also includes determining a verification value, and associating the permanent resource provider identifier with a token, the verification value, and domain controls. The method also includes providing a token data response message including a verification value to the token requestor, receiving an authorization request message comprising the token, the verification value, and one or more data elements in a plurality of data fields, determining the permanent resource provider identifier using the one or more data elements in the plurality of data fields, and determining that the verification value in the authorization request message matches the verification value that was provided to the token requestor, and that a transaction satisfies the domain controls.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
72.
System, Method, and Computer Program Product for Generating Synthetic Data
Provided are a method, system, and computer program product for generating synthetic data. The method includes generating a correlation graph of a plurality of data types based on a plurality of correlations. The method also includes generating a directed acyclic graph of the plurality of data types based on the correlation graph. The method further includes traversing the directed acyclic graph to produce a hierarchical graph of the plurality of data types, wherein the hierarchical graph includes a plurality of nodes, and wherein each node of the plurality of nodes is associated with a data type of the plurality of data types. The method further includes generating synthetic training data including a plurality of records of data by repeatedly traversing the hierarchical graph and based on a plurality of sets of values and a plurality of sets of interdependencies.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
A computer-implemented method performed by a user device is provided. The computer-implemented method includes receiving a message including an encrypted credential from a server computer; determining a response shared secret using a private key and a server public key; decrypting the encrypted credential using the response shared secret to determine a credential; obtaining a key derivation parameter from the credential; determining a first cryptogram key using the key derivation parameter; generating a first cryptogram using the first cryptogram key; and sending the first cryptogram to a second computer.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
Provided are systems for ensemble learning with machine learning models that include a processor to receive a training dataset of a plurality of data instances, wherein each data instance comprises a time series of data points, add an amount of time delay to one or more data instances to provide an augmented training dataset, select a first plurality of supervised machine learning models, select a second plurality of unsupervised machine learning models, train the first plurality of supervised machine learning models and the second plurality of unsupervised machine learning models based on the augmented training dataset, generate an ensemble machine learning model based on outputs of the supervised machine learning models and unsupervised machine learning models, and generate a runtime output of the ensemble machine learning model based on a runtime input to the ensemble machine learning model. Methods and computer program products are also provided.
A system includes a processor and a non-transitory computer readable medium coupled to the processor. The non-transitory computer readable medium comprises code that when executed by the processor, causes the processor to receive a money transfer amount indicative of an amount of funds to be transferred to a recipient. The processor generates a key code associated with the money transfer amount that is provided to a user of the system and given to the recipient by the user. The key code is programmed by the processor to enable the recipient to use the key code to redeem the amount of funds associated with the money transfer amount.
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
76.
OFFLINE SECURITY VALUE DETERMINATION SYSTEM AND METHOD
A method includes receiving, by a server computer, data of a communication device; training, by the server computer, a neural network model based on the data of the communication device and communication device metadata from one or more additional communication devices, to generate a machine learning model configured to determine, based on a metadata associated with an application, a security value related to an indication of a security threat; and transmitting the machine learning model to the communication device. The communication device can use the machine learning model to determine the security value, by inputting the metadata associated with the application, as a vectorized data into the machine learning model. The communication device can determine whether to run or install the application based upon the security value.
Systems, methods, and computer program products that use unsupervised learning to learn relationships between operations of a machine learning model based on a model graph representation to group the operations into clusters and, given a set of clusters and labels for the clusters, use a reinforcement learning algorithm to generate a final device placement result for the machine learning model.
Methods for updating an application programming interface (API) field of a transaction message may include receiving, with at least one processor, a payment transaction message, wherein the payment transaction message comprises data associated with a payment transaction; determining, with at least one processor, one or more API fields of the payment transaction message based on the data associated with the payment transaction; and modifying, with at least one processor, one or more API fields of the payment transaction message. Methods may also include transmitting, with at least one processor, a modified payment transaction message based on modifying the one or more API fields of the payment transaction message. Systems and computer program products are also disclosed.
Described are a system, method, and computer program product for wait time estimation using predictive modeling. The method includes receiving a request for a predictive wait time estimate from a user including a designated time and a selection of a merchant. The method also includes determining an initial queue length and determining a service rate for each subinterval of a plurality of subintervals from the current time to the designated time. The method further includes producing a plurality of arrival rates using a trained predictive model, and determining a difference between an arrival rate and a service rate for each subinterval, to produce a plurality of changes in queue length. The method further includes determining a queue length based on the plurality of changes in queue length, generating the predictive wait time estimate based on the queue length, and transmitting the predictive wait time estimate to the user.
A thin client may be utilized to facilitate data exchanges between two devices (e.g., a remote computer and a portable device). In some embodiments, the two devices may utilize differing communications protocols. The thin client may further be configured with a rules engine that determines one or more actions to be performed in response to one or more stimuli. The thin client may manage the processing flow between the two devices according to one or more predefined rules that are interpretable by the rules engine. The rules may be pushed to the thin client via any suitable device enabling the functionality of the thin client to be configured and/or modified without having to update the hardware and/or software of the thin client.
G06Q 20/20 - Systèmes de réseaux présents sur les points de vente
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
81.
System and Method for Processing Deferred Authorization Transactions
A method of processing a deferred authorization transaction including: receiving at least one transaction processing request associated with a transaction, where the transaction is initiated using a portable financial device associated with a user, the at least one transaction processing request including a deferred authorization indicator; determining that the at least one transaction processing request includes the deferred authorization indicator; determining that the transaction is a deferred authorization transaction based on determining that the at least one transaction processing request includes the deferred authorization indicator; and processing the transaction using at least one deferred authorization transaction rule in response to determining that the transaction is a deferred authorization transaction. A system for processing a deferred authorization transaction is also disclosed.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
82.
Model Management System for Developing Machine Learning Models
Provided is a system for developing a geographic agnostic machine learning model. The system may select transaction data associated with payment transactions conducted by a first plurality of users, wherein the transaction data includes first transaction data associated with payment transactions conducted by a first plurality of users in a first geographic area and second transaction data associated with payment transactions conducted by a second plurality of users in a second geographic area, normalize the first transaction data associated with payment transactions conducted by the first plurality of users in the first geographic area and the second transaction data associated with payment transactions conducted by the second plurality of users in the second geographic area to provide training data, generate a machine learning model using the training data, and determine a classification of an input using the machine learning model. A method and computer program product are also disclosed.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
83.
System, Method, and Computer Program Product for Implementing a Generative Adversarial Network to Determine Activations
Provided is a computer-implemented method for generating a machine learning model to classify an account based on merchant activation, including providing an input to a generator network of a generative adversarial network (GAN) to generate an output; providing the output as input to a discriminator network; providing a training dataset as input to the discriminator network; and updating the generator network based on a first output of the discriminator network having a label that indicates whether a set of values of each of the plurality of features is a real set of values or a fake set of values. The method may include updating the discriminator network based on a second output of the discriminator network having a label that indicates whether a selected account of the plurality of accounts is going to conduct a first payment transaction. A system and computer program product are also provided.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
Provided is a computer-implemented method, system, and computer program product for automatic selection of tests for software system regression testing using machine learning including generating a test mapping including at least one test of a plurality of tests corresponding to a source file. The plurality of tests and the at least one source file are associated with a software repository. Further, determining a defective score for the at least one test based on historical test data of the at least one test, receiving a component criticality score and a defect definition corresponding to the source file, generating a key value corresponding to at least one test based on the defective score, component criticality score, and defect definition, determining a subset of tests of the plurality of tests based on the key value corresponding to the at least one test; and executing the subset of tests with the software repository.
Described are a method, system, and computer program product for operating dynamic shadow testing environments for machine-learning models. The method includes generating a shadow testing environment operating at least two transaction services. The method also includes receiving a plurality of transaction authorization requests. The method further includes determining a first percentage associated with a first testing policy of the first transaction service and a second percentage associated with a second testing policy of the second transaction service. The method further includes replicating in the shadow testing environment, in real-time with processing the payment transactions, a first portion of the plurality of transaction authorization requests and a second portion of the plurality of transaction authorization requests. The method further includes testing the first transaction service using the first set of replicated transaction data and the second transaction service using the second set of replicated transaction data.
A first user device can transmit an interaction request to a remote computer via a long range communication channel. The first user device can receive an authentication request message from the remote computer and can then transmit the authentication request message to a second user device via a short range communication channel. The first user device can then receive an authentication response message comprising a response value from the second user device via the short range communication channel. The first user device can then transmit the authentication response message to the remote computer causing the remote computer to verify the response value and perform further processing if the response value is verified.
Provided is a method for normalizing embeddings for cross-embedding alignment. The method may include applying mean centering to the at least one embedding set, applying spectral normalization to the at least one embedding set, and/or applying length normalization to the at least one embedding set. Spectral normalization may include decomposing the at least one embedding set, determining an average singular value of the at least one embedding set, determining a respective substitute singular value for each respective singular value of a diagonal matrix, and/or replacing the at least one embedding set with a product of the at least one embedding set, a right singular vector, and an inverse of the substitute diagonal matrix. The mean centering, spectral normalization, and/or length normalization may be iteratively repeated for a configurable number of iterations. A system and computer program product are also disclosed.
G06F 5/01 - Procédés ou dispositions pour la conversion de données, sans modification de l'ordre ou du contenu des données maniées pour le décalage, p.ex. la justification, le changement d'échelle, la normalisation
Described are a system, method, and computer program product for reconfiguring a data table for processing on a server cluster. The method includes extracting a data table from a relational database and determining whether the data table includes a column having a range of values with a uniform distribution. The method also includes, in response to determining that the data table includes the column, classifying the column as a candidate column for splitting the data table. The method further includes, in response to determining that the data table does not include the column, inserting an index column into the data table and classifying the index column as the candidate column. The method further includes splitting the data table based on the candidate column and distributing each subdivision to a node of the server cluster so as to cause the server cluster to collectively process the data table.
Systems, methods, and computer program products for detecting merchant data shifts may identify a shift in transaction volume of a merchant system across Merchant Category Codes (MCCs) using a combination of time series analysis and machine learning.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
At an authorization server, a shared secret electronic key may be shared with a second computer. A selection to use a system to complete a transaction may be received from a first computing device. An image may be communicated to the first computing device. A digital representation entered by the user representing the image and a PIN based on the copy of the shared electronic key may be received from the second computing device. The system and method may determine if the digital representation entered by the user on the second computing device matches the image communicated to the first computing device. The system and method may determine if the PIN based on the copy of the shared electronic key from the second computing device is as expected. In response to determining the digital representation entered by the user matches the image and the PIN the second computing device is as expected, the user may be authorized.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
92.
Method, System, and Computer Program Product for Configuring at Least One Rule via a Graphical User Interface
Provided is a method for configuring at least one rule, e.g., using a graphical user interface. The method may include displaying a graphical user interface including a polygon having at least three edges and an icon at a first position within the polygon. Each edge of the polygon may be associated with a potential outcome of at least one rule. An input to move the icon to a second position within the polygon may be received. The graphical user interface may be displayed with the icon at the second position within the polygon. A distance from the second position of the icon to each edge of the polygon may be determined. The rule(s) may be adjusted based on the distance from the second position of the icon to each edge of the polygon. A system and computer program product are also disclosed.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06F 3/04847 - Techniques d’interaction pour la commande des valeurs des paramètres, p.ex. interaction avec des règles ou des cadrans
A method includes a validation computer receiving an authorization request message comprising a user state and a user proof from a user device. The user state comprises first and second user state elements. The user proof comprises first, second, and third user proof elements. The validation computer computes a first verification value by multiplying the first user proof element raised to the power of the second user state element, and the second user proof element raised to the power of the first user state element. The computer computes a second verification value by raising the second user proof element to the power of the second user state element. The computer compares the first verification value to a first accumulated state element of an accumulated state. The compares the second verification value to a second accumulated state element. The validation computer authorizes the authorization request message based on the comparison steps.
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
G06Q 20/06 - Circuits privés de paiement, p.ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
A method includes a server computer receiving a cryptogram request message comprising a token associated with a first credential during an interaction between a user of a user device and a resource provider of a resource provider application on the user device. The server computer generates a detokenization request message comprising the token. The server computer then provides the detokenization request message to a token service computer. The server computer receives a detokenization response message comprising a second credential from the token service computer. The server computer obtains a cryptogram for the interaction. The server computer generates a cryptogram response message comprising the second credential and the cryptogram, and then provides it in response to the cryptogram request message.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
95.
Method, system, and computer program product for local approximation of a predictive model
A method for local approximation of a predictive model may include receiving unclassified data associated with a plurality of unclassified data items. The unclassified data may be classified based on a first predictive model to generate classified data. A first data item may be selected from the classified data. A plurality of generated data items associated with the first data item may be generated using a generative model. The plurality of generated data items may be classified based on the first predictive model to generate classified generated data. A second predictive model may be trained with the classified generated data. A system and computer program product are also disclosed.
A processing system for fuel transactions analyzes transactions for symbols indicating a purchase amount and directs information about the purchase to a loyalty platform. The loyalty platform may identify and communicate in real time or near real time with a personal device associated with the purchaser of the fuel. A user interface of the personal device may allow the purchaser to review and select options for processing the fuel purchase using value from a loyalty program account. The selected option may be used to modify fuel purchase parameters prior to settlement of the transaction or simply add points to the user loyalty program account.
G06Q 30/0226 - Systèmes d’incitation à un usage fréquent, p.ex. programmes de miles pour voyageurs fréquents ou systèmes de points
B60S 5/02 - Alimentation des véhicules en combustible; Disposition générale des installations dans les stations d'approvisionnement
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06Q 30/0207 - Remises ou incitations, p.ex. coupons ou rabais
A user can associate a digital asset corresponding to a value with a transaction device to be used by another user. For example, a first user can load a digital asset corresponding to a cryptocurrency amount onto a transaction device, where the first user then provides the transaction device to a second user. The second user can utilize the cryptocurrency amount on the transaction device to conduct a transaction. The generation and use of digital assets can be managed using ledgers that store data in the form of block chains.
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/10 - Architectures de paiement spécialement adaptées aux systèmes de banque à domicile
G06Q 20/34 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des cartes, p.ex. cartes à puces ou cartes magnétiques
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/06 - Circuits privés de paiement, p.ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
98.
System, Method, and Computer Program Product for Real-Time Automatic Authorization of a Payment Transaction
Provided is a computer-implemented method for real-time automatic authorization of a payment transaction that is independent of an authorization input from a consumer. The method may include receiving first data associated with a consumer, generating a payment transaction classification model based on the first data associated with the consumer, receiving second data associated with the consumer, determining whether to process a payment transaction in real-time between the consumer and a merchant independent of an authorization input received from the consumer using the payment transaction classification model and the second data associated with the consumer, and processing a payment transaction between the consumer and the merchant based on determining to process the payment transaction in real-time between the consumer and the merchant.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
99.
System, Method, and Computer Program Product for Processing a Transaction as a Push Payment Transaction
Described are a system, method, and computer program product for processing a transaction as a push payment transaction. The method may include receiving, with a payment gateway processor, a transaction request from a merchant system. The transaction request may include transaction data associated with a payment device of a user, the payment device being associated with an issuer system. The method may also include generating, with the payment gateway processor, an authentication request based on the transaction data. The method may further include communicating, with the payment gateway processor, the authentication request to the issuer system. The method may further include, in response to the issuer system authenticating the authentication request, generating a push payment request including an account identifier associated with the merchant system, and communicating the push payment request to the issuer system.
G06Q 20/20 - Systèmes de réseaux présents sur les points de vente
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06Q 40/02 - Opérations bancaires, p.ex. calcul d'intérêts ou tenue de compte
Systems and methods are described for provisioning access credentials to a mobile device using device and authorization codes. Once provisioned, a mobile device can be used to conduct a transaction.
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
