Routing data in a data confidence fabric network. A confidence fabric adds confidence information to data delivered through the data confidence fabric network. A route is selected by considering inputs that include the trust insertion capabilities of nodes in potential routes, resource usage of nodes in the potential routes, and/or historical delivery times for the potential routes. One of the potential routes is selected as a selected route. The selected route may be based on best anticipated delivery time in view of the inputs.
Embodiments of the present disclosure provide a method, an electronic device, and a computer program product for virtual reality modeling. The method includes obtaining a first image of a real object at a first viewing angle. The method further includes obtaining, based on the first image, an initial three-dimensional model corresponding to the real object. The method further includes determining a second image of the real object at a second viewing angle different from the first viewing angle by using the initial three-dimensional model. The second image has texture characteristics of the real object. The method further includes generating a target three-dimensional model used for virtual reality and corresponding to the real object by using the second image and the first image. Through the solution, a three-dimensional model which can reproduce a real object with high quality may be obtained based on a small number of input images.
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p.ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersections; Analyse de connectivité, p.ex. de composantes connectées
3.
INTEGRATING CLUSTERED NETWORK ORCHESTRATOR WITH HOST CONFIGURATION PROTOCOLS
Integration of a clustered network orchestrator with host configuration protocols in a distributed node network system can be performed and managed. Respective nodes of the node network can generate, and store in a data store, respective network configuration reports (NCRs) based on respective portions of network configuration-related information relating to an external network host configuration protocol that are received from an external device by the respective nodes. A network management component (NMC) can determine a first network configuration of the network of nodes based on analysis of the NCRs, wherein the first network configuration relates to a first group of network addresses. NMC can determine a second network configuration of the network of nodes based on analysis of other network configuration-related information associated with an internal network configuration protocol associated with the node network, wherein the second network configuration relates to a second group of network addresses.
H04L 41/0894 - Gestion de la configuration du réseau basée sur des règles
H04L 41/0859 - Récupération de la configuration du réseau; Suivi de l’historique de configuration du réseau en conservant l'historique des différentes générations de configuration ou en revenant aux versions de configuration précédentes
Methods and systems for providing computer implemented services using configurable hardware components are disclosed. To update operation of a configurable hardware component, a large amount of data may be provided to a single input/output pin of the configurable hardware component. The large amount of data may be encoded in a complex waveform corresponding with at least eleven bits of digital data. The complex waveform may be interpreted by the configurable hardware component to obtain the large amount of data. Using the large amount of data, the configurable hardware component may update its operation to be in condition for providing the computer implemented services.
H02J 7/02 - Circuits pour la charge ou la dépolarisation des batteries ou pour alimenter des charges par des batteries pour la charge des batteries par réseaux à courant alternatif au moyen de convertisseurs
H02J 7/00 - Circuits pour la charge ou la dépolarisation des batteries ou pour alimenter des charges par des batteries
One example method includes determining that an application is running on a node of a data confidence fabric; performing an investigation to determine if the application is new to the data confidence fabric; when it is determined that the application is new to the data confidence fabric, generating an update comprising metadata that identifies the application and the node on which the application is running; and automatically deploying, to the node of the data confidence fabric, an application-specific plug-in configured to annotate data received from the application that was determined to be new to the data confidence fabric.
A storage device syndrome-weight-based error correction system includes a syndrome-weight-based error correction subsystem that is coupled to a storage subsystem in a chassis. The syndrome-weight-based error correction subsystem performs a first error correction hard decoding operation on the storage subsystem that utilizes first read voltage thresholds and that generates a first final codeword candidate having a first syndrome weight. The syndrome-weight-based error correction subsystem then performs error correction hard decoding read voltage threshold real-time search operations to determine second read voltage thresholds, and performs a second error correction hard decoding operation on the storage subsystem that utilizes the second read voltage thresholds and that generates a second final codeword candidate having a second syndrome weight. If the syndrome-weight-based error correction subsystem determines that the first syndrome weight is less than the second syndrome weight, it performs error correction soft decoding operations using the first read voltage thresholds.
H03M 13/15 - Codes cycliques, c. à d. décalages cycliques de mots de code produisant d'autres mots de code, p.ex. codes définis par un générateur polynomial, codes de Bose-Chaudhuri-Hocquenghen [BCH]
H03M 13/00 - Codage, décodage ou conversion de code pour détecter ou corriger des erreurs; Hypothèses de base sur la théorie du codage; Limites de codage; Méthodes d'évaluation de la probabilité d'erreur; Modèles de canaux; Simulation ou test des codes
H03M 13/11 - Détection d'erreurs ou correction d'erreurs transmises par redondance dans la représentation des données, c.à d. mots de code contenant plus de chiffres que les mots source utilisant un codage par blocs, c.à d. un nombre prédéterminé de bits de contrôle ajouté à un nombre prédéterminé de bits d'information utilisant plusieurs bits de parité
7.
METHOD AND SYSTEM FOR GENERATING MACHINE LEARNING TRAINING DATA STREAMS USING UNSTRUCTURED DATA
Techniques described herein relate to a method for managing training data. The method includes making a determination that the first stream request is associated with unstructured data; in response to the determination: obtaining a manifest associated with the unstructured data based on the stream request, wherein the manifest comprises metadata; loading the unstructured data into a cache using the manifest; merging the metadata with the unstructured data to generate training data, wherein the training data comprises a plurality of training data examples; generating augmented training data using the training data and the stream specification; generating a mini-batch sequence using the augmented training data and the stream specification; creating a mini-batch sequence queue and a stream endpoint; and streaming the mini-batch sequence using the mini-batch sequence queue and the stream endpoint, wherein the mini-batch sequence is used by a training environment to train a machine learning model.
G06F 7/14 - Interclassement, c. à d. association d'au moins deux séries de supports d'enregistrement, chacun étant rangé dans le même ordre de succession, en vue de former une série unique rangée dans le même ordre de succession
G06F 16/38 - Recherche caractérisée par l’utilisation de métadonnées, p.ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
8.
SYSTEM AND METHOD FOR MANAGEMENT OF INFERENCE MODELS BASED ON TRAINING DATA IMPACT ON MODEL REVERSION
Methods and systems for managing inference models are disclosed. The inference models may be used to provide computer implemented services by generating inferences used in the services. The inference models may be managed by reverting inference models that are found to be compromised through training with poisoned training data. The type of reversion and training data to be used may be selected based on the cost for performing the reversion and benefits provided by the reverted inference model using graphical user interfaces.
A self-healing Hard Disk Drive (HDD) system includes a chassis housing an HDD device self-healing subsystem coupled to an HDD data storage system that includes a plurality of HDD data storage resources. The HDD device self-healing subsystem prevents data from being stored on a first HDD data storage resource that is included in the plurality of HDD data storage resources included in the HDD data storage system. When the HDD device self-healing subsystem determines that data storage operations using a second HDD data storage resource that is included in the plurality of HDD data storage resources will be subsequently unavailable, it remaps logical addresses associated with the second HDD data storage resource to the first HDD data storage resource, and provides the data that was stored using the second HDD data storage resource on the first HDD data storage resource.
G06F 11/10 - Détection ou correction d'erreur par introduction de redondance dans la représentation des données, p.ex. en utilisant des codes de contrôle en ajoutant des chiffres binaires ou des symboles particuliers aux données exprimées suivant un code, p.ex. contrôle de parité, exclusion des 9 ou des 11
G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement
10.
PRECISE MULTI-STATE TUNING OF RECONFIGURABLE INTELLIGENT SURFACES UTILIZING ADVANCED MATERIALS
The technology described herein is directed towards phase-change material-based (e.g., chalcogenide) radio frequency components that can be used in unit cells of a reconfigurable intelligent surface. A multi-state tunable capacitive element for reconfigurable operation is described, in which phase-change material operates as a switching element to controllably vary capacitance of each unit cell. The multi-state tunable capacitive element can be made of multiple subcircuits in which capacitors of various values can be selectively switched in or out to vary the capacitance of the multi-state tunable capacitive element, resulting in a phase change of a unit cell with respect to reflecting or refracting an electromagnetic wave. By arranging the subcircuits with capacitors of different values, and actuating each one in or out of the overall capacitive element, an analog-like variable capacitor is provided to provide more granular phase shift control of cells of a reconfigurable intelligent surface.
H01G 7/00 - Condensateurs dont la capacité varie par des moyens non mécaniques; Procédés pour leur fabrication
H01Q 15/00 - Dispositifs pour la réflexion, la réfraction, la diffraction ou la polarisation des ondes rayonnées par une antenne, p.ex. dispositifs quasi optiques
H10N 70/20 - Dispositifs de commutation multistables, p.ex. memristors
11.
SYSTEM AND METHOD FOR MANAGEMENT OF INFERENCE MODELS BASED ON FEATURE CONTRIBUTION
Methods and systems for managing inference models are disclosed. The inference models may be used to provide computer implemented services by generated inferences used in the services. The inference models may be managed by proactively evaluating the inference models as they are updated over time. The inference models may be evaluated using user defined ranges for levels of contribution of features on output generated by the inference models. The user defined ranges may be established using a graphical user interface.
Techniques described herein relate to a method for managing training data. The method includes obtaining a first stream request, wherein the first stream request comprises a stream creation request and a stream specification; generating a new stream entry in a stream database; loading training data specified by the stream specification into a cache; generating a mini-batch sequence using the training data and the stream specification; creating a mini-batch sequence queue and a stream endpoint; generating mini-batch sequence access information associated with the mini-batch sequence; setting up a data transfer application programming interface (API) associated with the cache; and streaming the mini-batch access information to a client in a machine learning training environment using the mini-batch sequence queue and the stream endpoint, wherein the client uses the mini-batch sequence access information and the data transfer API to obtain mini batches of the mini-batch sequence.
G06F 12/0891 - Adressage d’un niveau de mémoire dans lequel l’accès aux données ou aux blocs de données désirés nécessite des moyens d’adressage associatif, p.ex. mémoires cache utilisant des moyens d’effacement, d’invalidation ou de réinitialisation
13.
RESOURCE UTILIZATION METADATA AND DATA CONFIDENCE FABRICS
One example method includes monitoring, by a profiler at a node of a data confidence fabric, resource consumption of one or more resources by the node in connection with operations performed by the node, performing a check to determine if resource consumption by the node is within a specified range, and based on an outcome of the check, assigning, or adjusting, a confidence score for the resource consumption. The confidence score may be used as a basis to perform one or more actions concerning the node and its workloads.
The described technology is generally directed towards resolving namespace collisions on a target system when applying incremental changes (e.g., between snapshots) as part of an incremental replication from a source system. Detected changes to a filesystem namespace include file link, directory move and file and directory unlink operations. The changes are processed to recognize and overcome failures and other issues, such as to not process an unlink before a corresponding link, which can otherwise result in accidental deletion of a file. Deferred operations are maintained for later processing, including deferred directory moves for directory rename failures, deferred unlink operations and name collision fixes. After initial processing, the deferred move list is iteratively processed to overcome directory rename failures, the deferred unlink list is processed after performing corresponding link operations, and the name fix list is processed to rename previously colliding names.
Embodiments of the present disclosure provide a method, an electronic device, and a computer program product for detecting a network attack. The method includes determining a compression ratio of written data in a time window of a predetermined time length, where the compression ratio is a ratio of a data amount of the written data before being compressed to a data amount of the written data after being compressed. The method further includes determining a user side connection associated with the written data at least according to determining that the compression ratio is less than a threshold compression ratio. In addition, the method includes determining data from the user side connection as a network attack according to determining that files associated with the user side connection cannot pass a file integrity check. Embodiments of the present disclosure can significantly reduce the computational amount of network attack detection.
Techniques described herein relate to a method for managing training data. The method includes obtaining a first stream request, wherein the first stream request comprises a stream creation request and a stream specification; in response to obtaining the stream creation request: generating a new stream entry in a stream database; loading training data specified by the stream specification into a cache; generating augmented training data using the training data and the stream specification; generating a mini-batch sequence using the augmented training data and the stream specification; creating a mini-batch sequence queue and a stream endpoint; and stream the mini-batch sequence using the mini-batch sequence queue and the stream endpoint, wherein the mini-batch sequence is used by a training environment to train a machine learning model.
G06F 12/0891 - Adressage d’un niveau de mémoire dans lequel l’accès aux données ou aux blocs de données désirés nécessite des moyens d’adressage associatif, p.ex. mémoires cache utilisant des moyens d’effacement, d’invalidation ou de réinitialisation
17.
RANSOMWARE DETECTION VIA MONITORING OPEN FILE OR PROCESS
A bait file owned by a bait process is created and locked in a computing system. Attempts or access the bait file or kill the bait process are detected. The process attempting to access the bait file or kill the bait process is viewed as malicious and protective operations are performed in the computing system. When an attempt to access the bait file is performed, the process attempting to access the bait file and all files related to the process attempting to access the bait file are identified. The related processes are identified using a table that tracks related processes. The protection operations are performed with respect to the process attempting to access the bait file and all related processes.
Time sensitive networking with data confidence is disclosed. Data ingested into a data confidence network is associated with annotations and/or confidence scores based on trust insertion technologies applied to the data. When time sensitive networking is applied, the annotations and confidence score reflect the application or use of time sensitive networking. Applications may determine whether to use or have confidence in the data based on the confidence score and/or annotations related to the use of time sensitive networking.
Methods and systems for managing collection of diagnostic data are disclosed. To collect diagnostic data, unmanaged devices may be used. The unmanaged devices may be registered with a data management system. During the registration process, procedures for processing diagnostic data from the unmanaged devices may be established. The procedures may be established based on data collection performance of the unmanaged devices. The procedures may reduce the likelihood of use of diagnostic data that is unreliable. To manage overhead for obtaining and maintaining data, a distributed inference model may be used to selective some diagnostic data for retention and other diagnostic data for removal. Once obtained, the diagnostic data may be rated for different uses based on the performance of the hardware used to obtain the diagnostic data.
Methods and systems for managing collection of diagnostic data are disclosed. To collect diagnostic data, unmanaged devices may be used. The unmanaged devices may be registered with a data management system. During the registration process, procedures for processing diagnostic data from the unmanaged devices may be established. The procedures may be established based on data collection performance of the unmanaged devices. The procedures may reduce the likelihood of use of diagnostic data that is unreliable. Once obtained, the diagnostic data may be rated for different uses based on the performance of the hardware used to obtain the diagnostic data. Access controls for the diagnostic data may be put in place to manage distribution of the diagnostic data.
A system comprises at least one camera disposed in an environment, and at least one computing node which hosts and executes an energy management system. The energy management system is configured to utilize computer vision processing of the images of the environment to extract information from the images, to utilize the extracted information from the images to determine usage patterns of light sources in the environment, and to generate intelligent recommendations for automated control of the light sources in the environment based on the determined usage patterns, to conserve energy consumption from use of the light sources in the environment.
G06V 20/52 - Activités de surveillance ou de suivi, p.ex. pour la reconnaissance d’objets suspects
G06V 10/60 - Extraction de caractéristiques d’images ou de vidéos relative aux propriétés luminescentes, p.ex. utilisant un modèle de réflectance ou d’éclairage
G06V 40/10 - Corps d’êtres humains ou d’animaux, p.ex. occupants de véhicules automobiles ou piétons; Parties du corps, p.ex. mains
22.
ARTIFICIAL AGING OF DIGITAL TWIN TO PREDICT POWER CONSUMPTION OF INFRASTRUCTURE
A method obtains at least one virtual representation of an infrastructure, wherein the virtual representation represents the infrastructure in a first state. The method applies a dataset to the virtual representation to artificially advance the virtual representation to represent the infrastructure in a second state. The method obtains results representing the infrastructure in the second state, responsive to applying the dataset to the virtual representation, wherein at least a portion of the results are indicative of a predicted power consumption associated with the infrastructure. The method initiates one or more actions with respect to the infrastructure in accordance with the predicted power consumption.
A method obtains at least one virtual representation representing an infrastructure in a first state and applies a first dataset to the virtual representation to artificially advance the virtual representation to represent the infrastructure in a second state. The method obtains results representing the infrastructure in the second state, wherein at least a portion of the results are indicative of a predicted condition associated with the infrastructure based on usage of the infrastructure. The method applies a second dataset to the virtual representation to artificially advance the virtual representation to represent the infrastructure in a third state and obtains results representing the infrastructure in the third state, wherein at least a portion of the results are indicative of an outcome to a solution applied via the second dataset to the predicted condition associated with the infrastructure.
Techniques for management of virtual representations (e.g., digital twins) of infrastructure are disclosed. For example, a method comprises obtaining at least one virtual representation of an infrastructure, wherein the virtual representation represents the infrastructure in a first state, and applying at least one dataset to the virtual representation to artificially advance the virtual representation to represent the infrastructure in a second state. The method further comprises obtaining results representing the infrastructure in the second state, responsive to applying the at least one dataset to the virtual representation, wherein at least a portion of the results are indicative of a cybersecurity issue on the infrastructure, and then initiating one or more of a remedial action and a preventative action with respect to the infrastructure to address the cybersecurity issue.
G06F 30/20 - Optimisation, vérification ou simulation de l’objet conçu
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p.ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
25.
DATA SOURCE CURATION AND SELECTION FOR TRAINING DIGITAL TWIN MODELS
A method identifies training data from at least one of a plurality of data sources, wherein the identified training data is determined to be suitable for a use case for which the model is to be used for representing the infrastructure. The method trains the model based on the identified training data. The method monitors at least one of a performance and an accuracy of the model. The method identifies different training data from at least one of the plurality of data sources, responsive to the monitoring, wherein the identified different training data is determined to be more suitable for the use case for which the model is to be used for representing the infrastructure. The method retrains the model based on the identified different training data.
G06F 30/27 - Optimisation, vérification ou simulation de l’objet conçu utilisant l’apprentissage automatique, p.ex. l’intelligence artificielle, les réseaux neuronaux, les machines à support de vecteur [MSV] ou l’apprentissage d’un modèle
26.
RETENTION LOCK LEVERAGING IN A BACKUP COMPUTING SYSTEM
One example method includes generating, by a data backup server agent that is hosted by a backup client computing system, backup data files from data stored at the backup client computing system. The backup data files are written to a temporary folder in a staging location of a backup storage server. A determination is made of if an attempt to move the temporary folder has failed. A failure is indicative that the backup storage server is operating in a retention lock mode. Each of the plurality of backup data files are moved individually from the temporary folder to a final folder in a final location of the backup storage server when it is determined that the attempt to move the temporary folder has failed.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p.ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
27.
METHOD AND SYSTEM FOR MANAGING FAILURE EVENTS OF A RECOVERY PROCESS USING A RECOVERY MODULE
A system for remediating a recovery process such as a migration of data includes an event database, a monitoring component, programmed to: monitor a source device to detect an initiation of a recovery process, wherein the recovery process is migration of application data from the source device to a target device, an analysis component programmed to: monitor the event database to detect a new event entry, wherein the event entry is associated with the recovery process of the source device, make a determination that the new event entry is associated with a failure event, based on the determination, provide the new event entry to a remediating component, programmed to obtain a recommendation for remediation based on the failure event and initiate the remediation based on the recommendation for remediation.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p.ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 11/07 - Réaction à l'apparition d'un défaut, p.ex. tolérance de certains défauts
28.
ACTIVE INFORMATION FOR USER DEVICES FOR IMPROVED SERVICE DELIVERY
A data communication network (100, 200, 400) includes a data communication node (120), an imaging device (130), and an information handling system (110, 300, 440). The data communication node (120) establishes a data connection with a user equipment device (160). The imaging device (130) provides image information for a coverage area associated with the data communication node (120). The information handling system (110, 300, 440) is coupled to the data communication node (120) and to the imaging device. The information handling system (110, 300, 440) receives the image information, synthesizes a 3D map of the coverage area based upon the image information, receives first coverage information from the first data communication node (120), correlates the first coverage information with the 3D map to generate a coverage map of the coverage area, to generate a first connectivity pattern associating a quality of connectivity provided by the first data communication node (120) within the coverage area, and determines a first location of the first user equipment device (160) within the connectivity pattern based on the image information.
G01S 5/16 - Localisation par coordination de plusieurs déterminations de direction ou de ligne de position; Localisation par coordination de plusieurs déterminations de distance utilisant des ondes électromagnétiques autres que les ondes radio
H04W 16/00 - Planification du réseau, p.ex. outils de planification de couverture ou de trafic; Déploiement de réseau, p.ex. répartition des ressources ou structures des cellules
H04W 36/32 - La resélection étant déclenchée par des paramètres spécifiques par des données de localisation ou de mobilité, p.ex. des données de vitesse
29.
SYSTEM AND METHOD FOR AUTHENTICATION IN A CLIENT-SERVER CONNECTION USING CHALLENGE APPLIED TO A SECRET KEY
A method for managing an authentication includes establishing, by a server device, a secured network channel with a client, providing, via the secured network channel, a private key to the client, after the providing, obtaining, from the client, a request for establishing a session with the client via a second network channel, in response to the request: sending a challenge request to the client, obtaining a challenge response associated with the challenge request, wherein the challenge response specifies a first challenge answer, performing a challenge processing using a private key to generate a second challenge answer, making a determination, using the first challenge answer and the second challenge answer, that the client is authenticated, and based on the determination, initiating the session with the client.
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
30.
BATTERY STATUS MONITORING AND BATTERY MANAGEMENT OF AN INFORMATION HANDLING SYSTEM
Managing a battery including measuring, in response to a first charging current and over a first time period, a first amperage and a first voltage of the cell at predetermined intervals; measuring, in response to a second charging current and over a second time period, a second amperage and a second voltage of the cell at the predetermined intervals; determining that the first amperage of the cell was maintained greater than a first threshold amount of time within the first time period, and in response, qualifying the first amperage and the first voltage as stable; determining that the second amperage of the cell was maintained greater than a second threshold amount of time within the second time period, and in response, qualifying the second amperage and the second voltage as stable; and in response to the qualifying, calculating a DCIR of the cell based on the voltages and the amperage.
A disclosed method retrieves a first set of time coordinated computing (TCC) attributes from firmware objects of an existing boot image and a second group of TCC attributes from firmware objects of an update boot image, such as a BKC firmware update. A runtime TCC attributes map is generated based on the first and second TCC attributes. Device-specific, TCC firmware objects are created for one or more devices based on the runtime TCC attributes map, and attributes of the one or more devices are tuned at OS runtime based on the device-specific time coordinated firmware objects. Disclosed teaching achieves silicon-agnostic seamless BKC firmware updates without compromising on platform performance against TCC attributes. At OS runtime, dynamic tuning to time TCC attributes for various system software modules which have a hard dependency on hardware/firmware can be achieved without a platform reboot.
Methods and systems for managing endpoint devices are disclosed. The endpoint devices may be managed by onboarding them. To onboarding the endpoint devices, ownership vouchers and proxy certificates may be used to cryptographically verify to which entities authority over the endpoint devices have been delegated. The proxy certificates may extend certificate and/or delegation chains in ownership vouchers to other devices. The extended chains may eliminate the need for proliferation of keys used to demonstrate authority over endpoint devices.
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
33.
RANSOMWARE DETECTION VIA DETECTING SYSTEM CALLS PATTERN IN ENCRYPTION PHASE
System calls performed by processes in a computing system are monitored and scored. The score is maintained over a time window. When the score exceeds a threshold score for a process in the time window, the process is determined to be a malware process and a protective operation is performed.
Techniques for resynchronizing storage resources of two sites configured for synchronous replication can include tracking in-progress write requests in a map. Responsive to a site failure or a replication link failure resulting in failure or fracture of the synchronous replication, processing can be performed to resynchronize impacted resources of the two sites configured for synchronous replication. The processing can use the in-progress write requests in combination with resource snapshots and snapshot differences to resynchronize the impacted resource of the two sites. In at least one embodiment, the synchronous replication configuration can include active paths between both sites and a host. In at least one embodiment, the synchronous replication configuration can include an active path between the host and one site, and a passive path between the host and the second site. The synchronous replication can be bi-directional or two-way synchronous replication between the two sites.
G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement
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
35.
METHOD AND SYSTEM FOR USER AUTHENTICATION DURING DATA MIGRATION
A method for performing a data migration operation includes scanning a target device to determine user accounts on the target device. The method also includes migrating data from a source device to the target device and monitoring user authentications of the user accounts on the target device while migrating data from the source device to the target device. Further, the method includes making a determination that a number of user authentications made while migrating data exceeds a threshold value, and stopping, based on the determination, migrating data from the source device to the target device.
The technology described herein is directed towards phase-change material-based (e.g., chalcogenide) radio frequency components that can be used in unit cells of a reconfigurable intelligent surface. A tunable device for reconfigurable operation is described, in which the operational width of phase-change material in the conductive state is controlled to controllably vary the phase shift of each unit cell. The width can be selectively controlled by heating elements that change the operational width of the material's lower-resistance state relative to its higher resistance state, resulting in a phase change of a unit cell with respect to redirecting an electromagnetic wave. By arranging the heating elements below the material, and actuating each one to provide resistive or conductive states within the overall unit cell surface, an analog-like device is provided to provide more granular phase shift control of the cells of a reconfigurable intelligent surface.
The technology described herein is directed towards phase-change material-based (e.g., chalcogenide) radio frequency components including for use in unit cells of a reconfigurable intelligent surface. A multi-state tunable capacitive element for reconfigurable operation is described, in which phase-change material operates as a switching element to controllably vary capacitance of each unit cell. The multi-state tunable capacitive element can be made of multiple subcircuits in which capacitors of various values can be selectively switched in or out to vary the capacitance of the tunable capacitive element. Arranging the subcircuits with capacitors of different values, and actuating each one in or out of the overall capacitive element, an analog-like variable capacitor is realized that provides more granular phase shift control of cells of a reconfigurable intelligent surface. When used with a dual split ring resonator capacitor, phase changes of a unit cell are achieved that redirect electromagnetic waves of two different frequencies.
A method for performing a data migration operation includes identifying data to be migrated from a source device to a target device. The method also includes determining a low risk level, a medium risk level, or a high risk level associated with each portion of the data and migrating the data associated with the low risk level to the target device, and, while migrating the data associated with the medium risk level to the target device, making a determination that a threat is present on the target device, where the threat is based on additional operations on the target device being indicative of suspicious activity. In addition, the method includes stopping, based on the determination, migrating the data associated with the medium risk level to the target device to the target device.
G06F 21/55 - Détection d’intrusion locale ou mise en œuvre de contre-mesures
G06F 21/54 - Contrôle des usagers, programmes ou dispositifs de préservation de l’intégrité des plates-formes, p.ex. des processeurs, des micrologiciels ou des systèmes d’exploitation au stade de l’exécution du programme, p.ex. intégrité de la pile, débordement de tampon ou prévention d'effacement involontaire de données par ajout de routines ou d’objets de sécurité aux programmes
G06F 21/56 - Détection ou gestion de programmes malveillants, p.ex. dispositions anti-virus
39.
FAIL-SAFE BOOT BLOCK TO DYNAMICALLY BOOT PLATFORM RESILIENCY FIRMWARE
A disclosed fail-safe boot block method leverages embedded controller (EC) functionality to monitor power on self-test (POST) messages and, in response to detecting a POST error message, execute a sequence of main basic input/output system (BIOS) recovery operations including, in at least some embodiments, performing top-block swap recovery features supported by the platform. If the main BIOS recovery operations fail to resolve the POST error issue, e.g., fail to resolve a No Boot/No Post/No Video (NB/NP/NV) state of the platform, a resiliency boot block bit is set and a reset is executed to boot the platform, via a fail-safe boot block, into the safe BIOS mode for error analysis and corrective action. The fail safe boot block and the safe BIOS firmware may reside in a flash partition that is factory-programmed and sealed to prevent substantially any subsequent programming and/or of the storage device. Additional benefit of the fail-safe boot features are disclosed herein.
G06F 11/22 - Détection ou localisation du matériel d'ordinateur défectueux en effectuant des tests pendant les opérations d'attente ou pendant les temps morts, p.ex. essais de mise en route
A system can receive a first request to list elements of a storage system that satisfy a search criterion. The system can determine to respond to the first request with a first page of results. The system can perform an iteration of identifying a group of results of the elements that satisfy the search criterion, wherein a number of results in the group of results is less than the limit, and wherein there is at least one result that is not included in the group of results. The system can, in response to determining that a threshold amount of time has elapsed relative to a timeout event associated with the first request, return the first page of results, wherein the first page of results comprises the group of results, and a token that is usable to identify the first request in a second request for a second page of results.
Methods and systems for managing inference models are disclosed. The inference models may be used to provide computer implemented services by generating inferences used in the services. The inference models may be managed by reverting inference models that are found to be compromised through training with poisoned training data. The type of reversion to be performed may be selected based on the cost for performing the reversion and benefits provided by the reverted inference model.
An information handling system may include a processor, one or more audio speakers configured to play back audible audio signals, and a basic input/output system (BIOS) comprising a program of instructions comprising boot firmware configured to be the first code executed by the processor when the information handling system is booted or powered on in order to initialize the information handling system for operation. The BIOS may be further configured to monitor for an error occurring during execution of the BIOS and responsive to an error occurring during execution of the BIOS, cause the one or more audio speakers to play back a sequence of one or more multi-frequency audio signals encoding an identity of the error.
Techniques described herein relate to a method for managing training data. The method includes monitoring, by a training data stream manager (TDSM), a cache comprising a plurality of training data examples associated with streams of mini-batch sequences scheduled to be transmitted to a machine learning training environment; making a first determination that a cache eviction is required; in response to the first determination: selecting a training data example of the plurality of training data examples; making a second determination that the training data example is eligible for cache eviction; in response to the second determination: evicting the training data example from the cache; and updating a training data example database entry to indicate that the training data example is evicted from the cache.
G06F 12/0891 - Adressage d’un niveau de mémoire dans lequel l’accès aux données ou aux blocs de données désirés nécessite des moyens d’adressage associatif, p.ex. mémoires cache utilisant des moyens d’effacement, d’invalidation ou de réinitialisation
G06F 12/0871 - Affectation ou gestion d’espace de mémoire cache
44.
ADAPTIVE COMPRESSION WITH PRE-FILTER CHECK FOR COMPRESSIBILITY TO IMPROVE READS ON A DEDUPLICATION FILE SYSTEM
Improving the performance of read operations in a restore path of an inline deduplication system utilizing a DDBOOST interface by providing an adaptive compression component for use with DDBOOST applications. A built-in compression mode transfers read data if there are sufficient CPU resources in the server and client to compress and decompress the read data without destabilizing the system. CPU usage is tracked to generate predicted respective client and server CPU usage. These respective predictions are compared to defined maximum threshold usage values. If the predicted values do not exceed the thresholds, compression is used, otherwise the data is transmitted over the network as non-compressed data. A pre-filter is used to first determine whether or not the data would benefit from the built-in compression mode.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p.ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 11/34 - Enregistrement ou évaluation statistique de l'activité du calculateur, p.ex. des interruptions ou des opérations d'entrée–sortie
A method comprises retrieving at least one file of a plurality of files from a source storage location, sending a request to a target storage location for metadata from an object corresponding to the same identifying information as that of the at least one file, and receiving a response from the target storage location, wherein content of the response is based on whether the object corresponding to the same identifying information as the at least one file is present in the target storage location.
The technology described herein is directed towards an autonomous reconfigurable intelligent surface (of a node) that is capable of detecting the node's surrounding environment and adjusting the redirection of impinging electromagnetic beams based on the detected environment. Real-time control of the reconfigurable intelligent surface is achieved from within the node itself, while the node consumes relatively little power. A LiDAR-based or other sensor coupled to the node provides a three-dimensional map of the environment's current state. Within the node, an AI module works with a controller to determine the phase of each reconfigurable unit-cell that forms the reconfigurable intelligent surface. The phase response of each cell redirects the impinging electromagnetic wave in the desired direction, e.g., to avoid an obstacle. This can significantly reduce coverage problems in the millimeter-wave band and even higher frequencies for beyond 5G and 6G applications.
G01S 17/894 - Imagerie 3D avec mesure simultanée du temps de vol sur une matrice 2D de pixels récepteurs, p.ex. caméras à temps de vol ou lidar flash
G01S 17/32 - Systèmes déterminant les données relatives à la position d'une cible pour mesurer la distance uniquement utilisant la transmission d'ondes continues, soit modulées en amplitude, en fréquence ou en phase, soit non modulées
47.
CALIBRATING A BATTERY OF AN INFORMATION HANDLING SYSTEM
Calibrating a battery including identifying a historical discharge rate of the battery; segmenting the historical discharge rate of the battery into regions; determining, based on the historical discharge rate of the battery, a first historical charge capacity of the battery for a first region and a second historical charge capacity of the battery for a second region; discharging, at an updated discharge rate, the battery from a first threshold voltage to a second threshold voltage; calculating, based on the updated discharge rate, a first updated charge capacity of the battery for the first region; determining a full charge capacity of the battery based on i) the first updated charge capacity of the battery for the first region and ii) the second historical charge capacity of the battery for the second region; adjusting a charging current of the battery based on the determined full charge capacity of the battery.
G01R 35/00 - Test ou étalonnage des appareils couverts par les autres groupes de la présente sous-classe
G01R 31/3842 - Dispositions pour la surveillance de variables des batteries ou des accumulateurs, p.ex. état de charge combinant des mesures de tension et de courant
H02J 7/00 - Circuits pour la charge ou la dépolarisation des batteries ou pour alimenter des charges par des batteries
48.
SYSTEMS AND METHODS FOR VALIDATING AUTHENTICITY OF DATABASES
Systems and methods for validating the authenticity of databases are described. In an illustrative, non-limiting embodiment, an Information Handling System (IHS) may include: a processor, and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the processor to: calculate a first hash of schema objects for a relational database; compare the calculated first hash of the schema objects with an expected second hash of the schema objects for the relational database; determine whether to validate of the relational database based, at least in part, on the comparison; and provide an indication of the determination to a recipient.
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 16/28 - Bases de données caractérisées par leurs modèles, p.ex. des modèles relationnels ou objet
49.
SYSTEM FOR THERMAL MANAGEMENT OF A HANDHELD COMPUTING DEVICE
A system for thermal management of a handheld computing device, including: a docking station, including: a first air inlet; a first air outlet; a first fan; the handheld computing device that is removably coupled to the docking station, including: a primary air outlet; a secondary air outlet including a vent door; a primary air inlet; a secondary air inlet; a DOO fan; wherein when the handheld computing device is coupled to the docking station: the first fan moves i) air from the first air inlet to the first air outlet to the secondary air inlet and ii) from the secondary air inlet to the secondary air outlet, and the fan i) moves air from the primary air inlet to the primary air outlet and ii) circulates air about the handheld computing device and to the secondary air outlet.
Methods and systems for managing collection of diagnostic data are disclosed. To collect diagnostic data, unmanaged devices may be used. The unmanaged devices may be registered with a data management system. During the registration process, procedures for processing diagnostic data from the unmanaged devices may be established. The procedures may be established based on data collection performance of the unmanaged devices. The procedures may reduce the likelihood of use of diagnostic data that is unreliable.
G16H 40/67 - TIC spécialement adaptées à la gestion ou à l’administration de ressources ou d’établissements de santé; TIC spécialement adaptées à la gestion ou au fonctionnement d’équipement ou de dispositifs médicaux pour le fonctionnement d’équipement ou de dispositifs médicaux pour le fonctionnement à distance
G16H 10/60 - TIC spécialement adaptées au maniement ou au traitement des données médicales ou de soins de santé relatives aux patients pour des données spécifiques de patients, p.ex. pour des dossiers électroniques de patients
G16H 40/40 - TIC spécialement adaptées à la gestion ou à l’administration de ressources ou d’établissements de santé; TIC spécialement adaptées à la gestion ou au fonctionnement d’équipement ou de dispositifs médicaux pour la gestion d’équipement ou de dispositifs médicaux, p.ex. pour planifier la maintenance ou les mises à jour
G16H 50/70 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicales; TIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour extraire des données médicales, p.ex. pour analyser les cas antérieurs d’autres patients
51.
RANSOMWARE DETECTION VIA MONITORING OPEN FILE OR PROCESS
A bait file owned by a bait process is created and locked in a computing system. Attempts or access the bait file or kill the bait process are detected. The process attempting to access the bait file or kill the bait process is viewed as malicious and protective operations are performed in the computing system.
The described technology is generally directed towards replicating a filesystem namespace from a source system such as a source node cluster to a target system such as a target node cluster. Directory transfer tasks processed at the source are sent to the target build a replica of a hierarchical namespace on a target cluster, in which the namespace contains the directories and files, with the file content temporarily absent. Files transfer tasks processed at the source are sent to the target to write the content into the files, generally after namespace creation is complete. Directory transfer is recursive, as one directory transfer task creates another directory transfer task for each of its child directories, and can be concurrent and sent as bulk transfer requests for efficiency in reducing overall latency overhead. File content transfer can transfer the content of multiple small files in a single transfer task request.
Methods and systems for managing collection of diagnostic data are disclosed. To collect diagnostic data, unmanaged devices may be used. The unmanaged devices may be registered with a data management system. During the registration process, procedures for processing diagnostic data from the unmanaged devices may be established. The procedures may be established based on data collection performance of the unmanaged devices. The procedures may reduce the likelihood of use of diagnostic data that is unreliable. Once obtained, the diagnostic data may be rated for different uses based on the performance of the hardware used to obtain the diagnostic data.
Techniques described herein relate to a method for managing metadata for unstructured data. The method includes identifying a first storage event associated with a first unstructured data object; streaming, from a storage resource, first system metadata associated with the first unstructured data object; identifying, using a first system metadata processor, a first object type associated with the first unstructured data object based on the first system metadata; storing the first system metadata in a first entry of a first metadata table; streaming second system metadata associated with a second unstructured data object; identifying, using the first system metadata processor, a second object type associated with the second unstructured data object based on the second system metadata; and storing the second system metadata in a second entry of a second metadata table, wherein the second metadata is queried to obtain the first unstructured data object.
G06F 16/38 - Recherche caractérisée par l’utilisation de métadonnées, p.ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
G06F 16/31 - Indexation; Structures de données à cet effet; Structures de stockage
SYSTEMS AND METHODS FOR AUTOMATICALLY PAIRING AN INFORMATION HANDLING SYSTEM (IHS) WITH A SELECTED ONE OF A PLURALITY OF WORKSPACE MANAGING DEVICES (WMDs) IN A SHARED WORK ENVIRONMENT
Systems and methods for automatically pairing an Information Handling System (IHS) to a selected one of a plurality of Workspace Managing Devices (WMDs) in a shared work environment are described. In an illustrative, non-limiting embodiment, an IHS may include an Embedded Controller (EC) and a memory coupled to the EC, the memory having program instructions stored thereon that, upon execution by the EC, cause the IHS to: perform a first wireless communication with a charging mat coupled to one of a plurality of WMDs disposed in a shared work environment, and establish a wireless connection with the WMD based, at least in part, upon first information exchanged over the first wireless communication.
G05B 19/05 - Automates à logique programmables, p.ex. simulant les interconnexions logiques de signaux d'après des diagrammes en échelle ou des organigrammes
A method obtains at least one virtual representation representing an infrastructure in a first state and applies a first dataset to the virtual representation to artificially advance the virtual representation to represent the infrastructure in a second state. The method obtains results representing the infrastructure in the second state, wherein at least a portion of the results are indicative of a predicted health condition associated with the infrastructure. The method applies a second dataset to the virtual representation to artificially advance the virtual representation to represent the infrastructure in a third state and obtains results representing the infrastructure in the third state, wherein at least a portion of the results are indicative of an outcome to a solution applied via the second dataset to the predicted health condition associated with the infrastructure.
G06F 30/20 - Optimisation, vérification ou simulation de l’objet conçu
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p.ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
57.
SYSTEMS AND METHODS PROVIDING SEAMLESS ACCESSIBILITY ACROSS PRE-BOOT AND RUNTIME ENVIRONMENTS
An operating system (OS) software service detects an accessibility change event and takes a snapshot of the accessibility settings before sending and receiving memory-mapped input/output (MMIO) commands with an embedded controller (EC) to establish trust using existing security hardening methods. The software service may send an MMIO command that includes the profile as a payload to the EC. The EC extracts the profile payload and saves it to an NVRAM variable before signaling a basic input/output system (BIOS) during early boot of an available accessibility profile. The EC publishes an accessibility profile presence to a BIOS pre-EFI initialization (PEI) layer, which sends a command to the EC to return the response. The BIOS creates a new hand off block (HOB) command indicative of the accessibility profile and passes this to an early Driver Execution Environment (DXE) stage, which reads the HOB data and locates the accessibility layer within a serial peripheral interface (SPI) firmware volume and loads into memory. This extracted profile information is passed onto the accessibility layer, which applies the profile data to user interface (UI) control attributes.
Memory management processes allocate and recycle pages of replication data pointer (RDP) metadata space in shared memory. When the RDP page currently allocated to an IO thread becomes full, that RDP page is released, and a new RDP page is allocated to the IO thread. The released page eventually becomes fragmented and is added to a list of RDP pages that are ranked based on partial fullness. An IO thread that needs a new RDP page is allocated a mostly empty RDP page from the ranked list, if such a page is available. Otherwise, a new completely empty RDP page is allocated to the IO thread. Use of the ranked lists reduces latency associated with allocation of new RDP pages. Contention between IO threads for RDP metadata space is reduced because each IO thread has exclusive rights to the free RDP metadata space in its currently allocated page.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p.ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 9/50 - Allocation de ressources, p.ex. de l'unité centrale de traitement [UCT]
59.
ARTIFICIAL AGING OF DIGITAL TWIN AS SOURCE FOR GAMIFICATION OF INFRASTRUCTURE
A method obtains at least one virtual representation of an infrastructure, wherein the virtual representation represents the infrastructure. The method applies, in a plurality of iterations, a plurality of simulated workloads to the virtual representation to artificially advance the virtual representation to generate a plurality of datasets respectively representing the infrastructure in a plurality of states. The method applies one or more gamification processes, between one or more of the plurality of iterations, to alter the corresponding one or more datasets generated by the virtual representation, wherein the one or more altered datasets are applied to the virtual representation along with one or more of the plurality of simulated workloads to represent the infrastructure in one or more subsequent states of the plurality of states. The method obtains gamification results representing the infrastructure, responsive to applying the one or more gamification processes.
Techniques for management of virtual representations (e.g., digital twins) of infrastructure are disclosed. For example, a method comprises obtaining at least one virtual representation of an infrastructure, wherein the virtual representation represents the infrastructure in a first state. The method further comprises applying at least one dataset to the virtual representation to artificially advance the virtual representation to represent the infrastructure in a second state. The method further comprises obtaining results representing the infrastructure in the second state, responsive to applying the at least one dataset to the virtual representation, wherein at least a portion of the results are indicative of an issue with the infrastructure, and then initiating one or more debugging actions with respect to the infrastructure to address the issue.
G06F 11/22 - Détection ou localisation du matériel d'ordinateur défectueux en effectuant des tests pendant les opérations d'attente ou pendant les temps morts, p.ex. essais de mise en route
61.
Server System Open Compute Project Mounting System
A floating open compute project retention system. The floating open compute project retention system includes a floating open compute project component guide device and a floating open compute project component retention device, the floating open compute project component retention device providing access to the floating open compute project component guide device when in an open position and fixedly mounting a floating open compute project receiving assembly within an open compute project mounting bay when in a closed position.
A bait file owned by a bait process is created and locked in a computing system. Attempts or access the bait file or kill the bait process are detected. The process attempting to access the bait file or kill the bait process is viewed as malicious and protective operations are performed in the computing system. At times, ownership of the bait file is switched to a different process, which may encourage the malicious process to attempt access and thereby be detected.
A storage device syndrome-weight-based error correction system includes a syndrome-weight-based error correction subsystem coupled to a storage subsystem in a chassis. The syndrome-weight-based error correction subsystem performs a plurality of respective first error correction hard decoding operations on the storage subsystem that each utilize respective read voltage thresholds and that each generate a respective final codeword candidate having a respective syndrome weight. The syndrome-weight-based error correction subsystem identifies a first syndrome weight of a first final codeword candidate that was generated via the performance of one of the plurality of respective first error correction hard decoding operations that utilized first read voltage thresholds and that is lower than the syndrome weights of the final codeword candidates generated via the performance of the others of the plurality of respective first error correction hard decoding operations, and performs error correction soft decoding operations using the first read voltage thresholds.
H03M 13/11 - Détection d'erreurs ou correction d'erreurs transmises par redondance dans la représentation des données, c.à d. mots de code contenant plus de chiffres que les mots source utilisant un codage par blocs, c.à d. un nombre prédéterminé de bits de contrôle ajouté à un nombre prédéterminé de bits d'information utilisant plusieurs bits de parité
64.
SECURE METHOD OF BI-DIRECTIONAL INLINE EXCHANGE OF CRYPTOGRAPHIC CERTIFICATES FOR DATA TRANSFERS
Embodiments for securely exchanging Certificate Authority (CA) certificates inline and bi-directionally to make it easier for client-server transmissions to use certificate-based authentication. The client certificate is transferred securely through encryption with a pre-shared key based on certain parameters, and the server certificate is transferred securely through encryption with a pre-shared key based on the parameters. The process reduces the burden from applications to maintain and save the CA certificate. It also reduces the burden from server to maintain and save the CA certificate of the client so that server can select it to be used during authentication. This helps enable large scale deployments where the server can maintain the CA certificate and send it to client.
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 data communication network (100, 200, 400) includes a data communication node (120, 412, 414, 422, 424, 432, 434), an imaging device (130), and an information handling system (110, 300, 440). The data communication node (120, 412, 414, 422, 424, 432, 434) establishes a data connection with a user equipment device (160). The imaging device provides image information for a coverage area associated with the data communication node (120, 412, 414, 422, 424, 432, 434). The information handling system (110, 300, 440) is coupled to the data communication node (120, 412, 414, 422, 424, 432, 434) and to the imaging device. The information handling system (110, 300, 440) receives the image information, synthesizes a 3D map of the coverage area based upon the image information, receives first coverage information from the first data communication node (120, 412, 414, 422, 424, 432, 434), correlates the first coverage information with the 3D map to generate a coverage map of the coverage area, and determines a first location of the first user equipment device (160) within the coverage map based on the image information.
G01S 5/16 - Localisation par coordination de plusieurs déterminations de direction ou de ligne de position; Localisation par coordination de plusieurs déterminations de distance utilisant des ondes électromagnétiques autres que les ondes radio
H04W 16/00 - Planification du réseau, p.ex. outils de planification de couverture ou de trafic; Déploiement de réseau, p.ex. répartition des ressources ou structures des cellules
H04W 36/32 - La resélection étant déclenchée par des paramètres spécifiques par des données de localisation ou de mobilité, p.ex. des données de vitesse
A data communication network (100, 200, 400) includes data communication nodes (120), imaging devices (130), and an information handling system (110, 300, 430). The nodes establish data connections with user equipment devices (160). The imaging devices (130) provide image information for a coverage area of the network. The information handling system (110, 300, 430) synthesizes a 3D map of the coverage area based upon the image information, determines that a first region of the 3D map is an inactive region of an emergency response incident and determines that a second region of the 3D map is an active region of the emergency response incident based on the image information, and directs a group of user equipment devices (160) to the inactive region.
H04B 7/06 - Systèmes de diversité; Systèmes à plusieurs antennes, c. à d. émission ou réception utilisant plusieurs antennes utilisant plusieurs antennes indépendantes espacées à la station d'émission
G08B 27/00 - Systèmes d'alarme dans lesquels la condition déclenchant l'alarme est signalée par une station centrale à plusieurs sous-stations
G08B 7/06 - Systèmes de signalisation selon plus d'un des groupes ; Systèmes d'appel de personnes selon plus d'un des groupes utilisant une transmission électrique
67.
Method and system for data protection and data availability
A method for managing data availability includes making a first determination by a first security module (FSM) that a first storage area network (SAN) infrastructure in a first data center has experienced a failure. The method also includes generating a secure string based on a first configuration parameter. Further, the method includes appending the secure string to a SAN failure notification to generate a secure string-appended request. In addition, the method includes sending the secure string-appended request to a second data center, wherein the second data center is selected based on a second configuration parameter. Moreover, the method includes making a second determination that the encrypted secure string-appended request is valid. Further, the method includes offloading processing of requests sent to the first data center using the second data center.
G06F 11/20 - Détection ou correction d'erreur dans une donnée par redondance dans le matériel en utilisant un masquage actif du défaut, p.ex. en déconnectant les éléments défaillants ou en insérant des éléments de rechange
Methods and systems for managing systems based on power consumption are disclosed. To operate data processing systems, power may be supplied to the systems. Power supply capacity may be provisioned based on the estimated power consumption for the systems. To estimate the power consumption of the systems, limits on the operation of components of the systems may be taken into account. These limits may reduce the power consumption by the components from nominal power consumption ascribed by a manufacturer. The limits may be caused by the communication architecture or other features of the systems.
A method for efficient file-based backups and recoveries. The method includes: receiving, to initiate a backup session, a file-system backup instruction identifying a host file-system; obtaining at least one clone logical cluster number (LCN) corresponding to a file managed by the host file-system, and a region LCN corresponding to a file region of the file; based on a determination that the region LCN matches a clone LCN of the at least one clone LCN: querying a cluster-offset tracking data structure using the region LCN to identify a cluster-offset tracking entry including the region LCN and a container offset; writing, as a session metadata record stored in backup session metadata for the backup session, file metadata describing the file and including the container offset; and transmitting, to a backup target, an information tuple including a backup session identifier generated for the backup session, and the backup session metadata.
G06F 16/00 - Recherche d’informations; Structures de bases de données à cet effet; Structures de systèmes de fichiers à cet effet
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p.ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 16/11 - Administration des systèmes de fichiers, p.ex. détails de l’archivage ou d’instantanés
G06F 16/14 - Systèmes de fichiers; Serveurs de fichiers - Détails de la recherche de fichiers basée sur les métadonnées des fichiers
71.
AUTOMATICALLY MODIFYING USER CODE USING ARTIFICIAL INTELLIGENCE TECHNIQUES
Methods, apparatus, and processor-readable storage media for automatically modifying user code using artificial intelligence techniques are provided herein. An example computer-implemented method includes obtaining user-provided code and one or more items of information associated with the user-provided code; determining code functionality information and one or more execution-related details associated with the user-provided code by processing at least a portion of the user-provided code and at least a portion of the items of information using artificial intelligence techniques; generating one or more code segments, related to one or more portions of the user-provided code, by processing the code functionality information and the execution-related detail(s) using the artificial intelligence techniques; executing at least a portion of the code segment(s) in at least one simulation environment; and performing one or more automated actions based on results from executing the at least a portion of the code segment(s).
Methods, apparatus, and processor-readable storage media for automatically determining authenticated online statuses of edge devices are provided herein. An example computer-implemented method includes authenticating at least one connection of at least one edge device to at least one event bus by processing at least one event communication signed by the at least one edge device; storing the at least one signed event communication in at least one database; requesting online status of the at least one edge device by querying one or more APIs associated with the at least one event bus in accordance with one or more temporal parameters; comparing one or more responses from the one or more APIs associated with the at least one event bus with at least a portion of the at least one signed event communication stored in the at least one database; and performing automated actions based on the comparing.
A method comprises receiving an input string comprising one or more identifiers for an operation, and searching at least one data repository for files corresponding to the one or more identifiers. Similarities between the input string and respective ones of the files corresponding to the one or more identifiers are computed, and the files corresponding to the one or more identifiers are ranked based on the computed similarities. The method further comprises grouping at least a portion of the ranked files into at least one group based on the one or more identifiers. At least one division in a logical drive of the at least one data repository is generated, wherein the at least one division corresponds to the at least one group and comprises at least the portion of the ranked files of the at least one group.
G06F 16/28 - Bases de données caractérisées par leurs modèles, p.ex. des modèles relationnels ou objet
G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
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
74.
CACHING TECHNIQUES USING A UNIFIED CACHE OF METADATA LEAF OBJECTS WITH MIXED POINTER TYPES AND LAZY CONTENT RESOLUTION
Techniques for processing a read I/O operation directed to a logical address LA1 can include: determining a logical address range R1 including LA1; determining whether a unified cache includes a cached object corresponding to R1; and responsive to determining that the unified cache does not include a cached object corresponding to R1, determining a unified cache miss with respect to R1 and performing unified cache miss processing including: traversing metadata pages, including a metadata leaf page, corresponding to LA1; storing indirect pointers from entries of the metadata leaf page to corresponding entries of a new metadata leaf object of the unified cache corresponding to R1; performing processing using an indirect pointer of an entry of the new metadata leaf object, where the entry corresponds to LA1 and the processing includes retrieving the content of LA1 using the indirect pointer; and returning the content in response to the read I/O operation.
G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement
G06F 12/0802 - Adressage d’un niveau de mémoire dans lequel l’accès aux données ou aux blocs de données désirés nécessite des moyens d’adressage associatif, p.ex. mémoires cache
Methods, apparatus, and processor-readable storage media for controlling transfer of data based on network bandwidth demand are provided herein. An example method includes obtaining a request to transfer data corresponding to an application by at least one node of a plurality of nodes of a distributed computing system; identifying a category of the data, from among a plurality of categories, to be transferred by the application based on the request; and controlling the transfer of the data based on the identified category, where the controlling includes: causing the at least one node to transfer the data in response to the identified category being a first category of a plurality of categories; and causing the at least one node to at least delay the transfer of the data based on the category being a different category of the plurality of categories and an available network bandwidth of the distributed computing system.
H04L 67/1014 - Sélection du serveur pour la répartition de charge basée sur le contenu d'une demande
H04L 47/10 - Commande de flux; Commande de la congestion
H04L 47/283 - Commande de flux; Commande de la congestion par rapport à des considérations temporelles en réponse à des retards de traitement, p.ex. causés par une gigue ou un temps d'aller-retour [RTT]
76.
SYSTEM AND METHOD FOR CANCER IDENTIFICATION USING GENERATIVE ADVERSARIAL NETWORKS AND IMAGE ENTROPY
A prognosis system is programmed to: obtain, from a biomarker image generation service, a set of original biomarker images, generate a set of synthetic images using the set of original biomarker images, perform an entropy calculation on each of the set of synthetic images to obtain a set of entropy images, apply an entropy thresholding on the set of entropy images to obtain a set of threshold images, apply a masking on the set of threshold images to obtain a pair of masked images for each of the set of threshold images, compare each of the pair of masked images using a cosine similarity (CS) value to assign a cancer value to a corresponding threshold image of the set of threshold images, and based on the cancer value, determine a cancer prognosis to each of the synthetic images.
Methods and systems for authenticating data processing systems throughout a distributed environment without user intervention are disclosed. To authenticate data processing systems without user intervention, a system may include a network core and one or more data processing systems. A previously established root of trust between the network core and a data processing system may be lost and the network core may attempt to re-authenticate the data processing system using a security questionnaire. Security questions included in the security questionnaire may be based on historical telemetry data and may be chosen based on a degree of variability of features of the telemetry data. The network core may provide the data processing system with a security questionnaire and the data processing system may use similar telemetry data to respond to the security questionnaire. If the answers to the security questions are considered accurate, the data processing system may be re-authenticated.
Methods and systems for authenticating data processing systems throughout a distributed environment without user intervention are disclosed. To authenticate data processing systems without user intervention, a system may include a network core and one or more data processing systems. Data processing systems may provide telemetry data to the network core for use in future authentication processes. To increase security throughout the system, the network core may ensure that low security data points are not retained for authentication. A low security data point may be a data point that matches a data point obtained from another data processing system. If a root of trust is lost between a data processing system and the network core, the network core may use retained telemetry data points to generate a security questionnaire. If the data processing system successfully answers security questions of the security questionnaire, the root of trust may be restored.
Methods and systems for authenticating data processing systems throughout a distributed environment without user intervention are disclosed. To authenticate data processing systems without user intervention, a system may include a network core and one or more data processing systems. A previously established root of trust between the network core and a data processing system may be lost and the network core may attempt to re-authenticate the data processing system using a security questionnaire. Security questions included in the security questionnaire may be based on historical telemetry data and may be chosen based on a degree of anomalousness of data points of the telemetry data. The network core may provide the data processing system with a security questionnaire and the data processing system may use similar telemetry data to respond to the security questionnaire. If the answers to the security questions are considered accurate, the data processing system may be re-authenticated.
One example method includes monitoring pagination operations of an operating system, collecting information about the pagination operations, analyzing the information about the pagination operations, and based on the analyzing, determining whether any of the pagination operations are indicative of a malicious service. When the pagination operations are different from what is expected when only legitimate services are running, an inference is made that some of the pagination operations are indicative of ransomware.
Methods (and systems) described herein provide a specialized technique for automatically scaling resources that provide data protection services to client systems. In some embodiments, the resource units (or pods) may be deployed on a platform (e.g., platform-as-a-service, or PaaS), which provides containerized services (and workloads) as part of a clustered computing environment (e.g., Kubernetes). The technique may scale the number of resource units used to perform data protection operations based on specialized criteria. For example, a particular service (e.g., redirection service) that utilizes resource units (e.g., pods) to perform functions may automatically increase (or decrease) the number resource units available to handle data management operations originating from the client systems.
H04L 47/80 - Actions liées au type d'utilisateur ou à la nature du flux
H04L 47/70 - Contrôle d'admission; Allocation des ressources
H04L 47/762 - Contrôle d'admission; Allocation des ressources en utilisant l'allocation dynamique des ressources, p.ex. renégociation en cours d'appel sur requête de l'utilisateur ou sur requête du réseau en réponse à des changements dans les conditions du réseau déclenchée par le réseau
One example method includes identifying a candidate process for monitoring, while the candidate process is running, taking a set of snapshots of the candidate process, and each of the snapshots corresponds to a respective time period during which the candidate process was running, analyzing the snapshots to determine whether the candidate process comprises a ransomware process, and when a counter indicates that the candidate process includes a number of write operations that exceeds a threshold, the candidate process is identified as a ransomware process.
G06F 21/56 - Détection ou gestion de programmes malveillants, p.ex. dispositions anti-virus
G06F 21/53 - Contrôle des usagers, programmes ou dispositifs de préservation de l’intégrité des plates-formes, p.ex. des processeurs, des micrologiciels ou des systèmes d’exploitation au stade de l’exécution du programme, p.ex. intégrité de la pile, débordement de tampon ou prévention d'effacement involontaire de données par exécution dans un environnement restreint, p.ex. "boîte à sable" ou machine virtuelle sécurisée
One example method includes receiving, at a node of a data confidence fabric, data from a data source, determining, by the node, whether the data source is listed in a portfolio of data sources, when the data source is listed in the portfolio, processing, by the node, the data, when the data source is not listed in the portfolio, performing, by the node, an analysis of the data, when the analysis reveals that the data is recognized by the node, processing, by the node, the data, and when the analysis reveals that the data is not recognized by the node, performing an action.
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p.ex. par clés ou règles de contrôle de l’accès
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p.ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
One example method includes receiving, at a node of a data confidence fabric, a data stream, prepending, by the node, a data confidence fabric header to the data stream so as to create a prepended data stream, and the data confidence fabric header includes confidence metadata relating to the data stream, and transmitting, by the node, the prepended data stream to another node of the data confidence fabric. The confidence metadata includes metadata about hardware and/or software associated with the data in the data stream.
One example method includes monitoring a file access request made by a process, searching, in a pointer array that corresponds to the process, for a pointer to the file that was requested by the process, when the pointer is found in the pointer array, incrementing a score associated with the process, performing an anomaly detection check, and when an anomaly is detected, blocking access to the file by the process, and when no anomaly is detected, updating the pointer array to include a pointer to the file to which access was requested by the process.
Embodiments of the present disclosure relate to a method, a device, and a computer program product for data backup. The method includes determining a group of backup tasks for backing up a data object. The method further includes determining, based on backup types of backup tasks in the group of backup tasks, whether there are a plurality of backup tasks capable of being combined in the group of backup tasks. The method further includes determining, in response to determining that there are a plurality of backup tasks capable of being combined in the group of backup tasks, a combined backup task for the plurality of backup tasks. The method further includes backing up the data object by using the combined backup task. This method can reduce the amount of data that needs to be backed up, thereby reducing the use of computing resources and storage resources, reducing the impact on a production environment of a user, and improving the user experience.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p.ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
87.
METHOD, ELECTRONIC DEVICE, AND COMPUTER PROGRAM PRODUCT FOR DATA PROCESSING
Techniques perform data processing. Such techniques involve obtaining, by a first operating system, first data of a storage system from a data collector. Such techniques further involve synchronizing the first data from the first operating system to a second operating system, wherein an architecture of the second operating system is different from that of the first operating system. Such techniques further involve, in response to that the first operating system has a failure, obtaining, by the second operating system, second data of the storage system from the data collector. Such techniques further involve, in response to that the first operating system is recovered, synchronizing the second data from the second operating system to the first operating system. Accordingly, such techniques can minimize processing time, ensure high availability of data collection, save computing and memory resources of a storage system, and help improve user experience.
An information handling system main board CMOS is powered by a CMOS battery, such as to keep a real time clock during a power off state, with the battery ground passed through a ground pad so that ground to the CMOS is incomplete until a coupling device, such as a screw, couples the main board to an information handling system housing. A bi-stable relay couples to the main board between the CMOS battery positive terminal and the CMOS to prevent application of power by the CMOS battery to the CMOS after closing of the ground until an embedded controller that is powered on the main board commands closing of the bi-stable relay.
G06F 1/26 - Alimentation en énergie électrique, p.ex. régulation à cet effet
G06F 1/14 - Dispositions pour le contrôle du temps, p.ex. horloge temps réel
G06F 1/18 - Installation ou distribution d'énergie
G06F 1/3287 - Gestion de l’alimentation, c. à d. passage en mode d’économie d’énergie amorcé par événements Économie d’énergie caractérisée par l'action entreprise par la mise hors tension d’une unité fonctionnelle individuelle dans un ordinateur
89.
DEMODULATION REFERENCE SIGNAL BASED CHANNEL ESTIMATION FOR ADJUSTING OR STOPPING RETRANSMISSION
Demodulation reference signal (DMRS) based channel estimation, e.g., for adjusting and/or stopping retransmissions, is described herein. A method as described herein can include receiving, by a device comprising a processor, a first transmission that is transmitted to the device by network equipment via a downlink channel, wherein the first transmission comprises a DMRS; estimating, by the device, a channel quality associated with the downlink channel based on the DMRS, resulting in an estimated channel quality; and transmitting, by the device to the network equipment via an uplink channel, a second transmission, the second transmission comprising channel quality data indicative of the estimated channel quality and hybrid automatic repeat request data corresponding to the first transmission.
H04L 1/1607 - Dispositions pour détecter ou empêcher les erreurs dans l'information reçue en utilisant un canal de retour dans lesquelles le canal de retour transporte des signaux de contrôle, p.ex. répétition de signaux de demande - Détails du signal de contrôle
90.
BEAMFORMING OPTIMIZATION TO ADAPT TO ENVIRONMENTAL CHANGES AND RF CONSUMPTION PATTERNS
A data communication network (100, 200) includes data communication nodes (120) configured to establish data connections with user equipment devices (160) within a RF coverage area, imaging devices (130) configured to provide image information for the RF coverage area, and an information handling system (300). The information handling system (110, 300) receives RF coverage information from the data communication nodes (120), receives first image information from the imaging devices (130), determines a first RF coverage map for the RF coverage area based upon the RF coverage information and the image information, provides a first bandwidth allocation to the data communication nodes (120) based on the first RF coverage map, receives second image information from the imaging devices (130), determines that the first RF coverage map has changed to a second RF coverage map based upon a difference between the first image information and the second image information, and provides a second bandwidth allocation to the data communication nodes (120) based on the second RF coverage map.
H04W 64/00 - Localisation d'utilisateurs ou de terminaux pour la gestion du réseau, p.ex. gestion de la mobilité
H04W 16/28 - Structures des cellules utilisant l'orientation du faisceau
H04W 4/029 - Services de gestion ou de suivi basés sur la localisation
H04W 36/32 - La resélection étant déclenchée par des paramètres spécifiques par des données de localisation ou de mobilité, p.ex. des données de vitesse
H04B 7/06 - Systèmes de diversité; Systèmes à plusieurs antennes, c. à d. émission ou réception utilisant plusieurs antennes utilisant plusieurs antennes indépendantes espacées à la station d'émission
91.
PATTERN LEARNING TO ELIMINATE REPETITIVE COMPUTE OPERATIONS IN A DATA COMMUNICATION NETWORK
A data communication network includes a first data communication node (120) configured to establish a first data connection with a user equipment device (160) within a coverage area of the data communication network, a second data communication node (120) configured to establish a second data connection with the user equipment device (160) within the coverage area, an imaging device (130) configured to provide image information for the coverage area, and an information handling system (110, 300). The information handling system (110, 300) determines a trajectory of the user equipment device (160) within the coverage area based upon the image information, and determines a location along the first trajectory to hand off the user equipment device (160) from the first data connection to the second data connection based on the first trajectory.
H04W 4/02 - Services utilisant des informations de localisation
H04W 36/32 - La resélection étant déclenchée par des paramètres spécifiques par des données de localisation ou de mobilité, p.ex. des données de vitesse
H04W 64/00 - Localisation d'utilisateurs ou de terminaux pour la gestion du réseau, p.ex. gestion de la mobilité
Techniques of the present disclosure can include: identifying blocks of storage available for allocation; generating a list denoting an allocation order of storage chunks of the blocks; receiving a write I/O operation that writes data to a first logical address; allocating a storage chunk in accordance with the allocation order of the list, wherein a first block includes the storage chunk and a second storage chunk; storing the first data in the storage chunk of the first block; removing the second storage chunk from the list; and creating a mapping between the first logical address and the first block indicating the second storage chunk is reserved for storing content written to a logical address included in a volume logical address range comprising the first logical address. The allocation order can spread allocation distance between blocks and chunks of the same block to avoid contention during flushes.
Methods, apparatus, and processor-readable storage media for automatically generating device-related temporal predictions using artificial intelligence techniques are provided herein. An example computer-implemented method includes obtaining data pertaining to one or more aspects of at least one device-related repair task; generating one or more device-related temporal predictions associated with the at least one device-related repair task by processing at least a portion of the obtained data using one or more artificial intelligence techniques; and performing one or more automated actions based at least in part on at least a portion of the one or more device-related temporal predictions.
A method comprises receiving a request to log at least one operation of a plurality operations, wherein the request includes one or more features of the at least one operation. The one or more features are analyzed using one or more machine learning algorithms. The method further comprises selecting, based at least in part on the analyzing, a log provider of a plurality of log providers to log the at least one operation, and interfacing with the log provider to enable logging of the at least one operation.
G06F 16/38 - Recherche caractérisée par l’utilisation de métadonnées, p.ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
Methods, apparatus, and processor-readable storage media for identifying applications impacted by request-related attribute changes are provided herein. An example method includes obtaining one or more changes to an attribute of a first application, wherein the at least one attribute is used by one or more of a plurality of applications to process a request associated with the attribute; determining one or more other attributes used by the plurality of applications that are dependent on the attribute; generating a dependency model for the attribute based at least in part on the one or more other attributes and dependency relationships between the plurality of applications; identifying one or more of the plurality of applications that are impacted by the one or more changes to the attribute based on the dependency model; and initiating one or more automated actions based on the identified one or more applications.
Embodiments of the present disclosure relate to a method, a device, and a computer program product for generating a three-dimensional (3D) object model. The method includes generating a first 3D object model based on multiple two-dimensional (2D) images of an object in different views. The method further includes acquiring metadata related to the first 3D object model by searching for information related to the object in at least one of a database and the Internet. The method further includes generating a second 3D object model by combining the first 3D object model and the metadata. The method for generating a 3D object model according to the present disclosure can automatically generate customizable and editable 3D model metadata, thereby significantly reducing labor, saving costs, improving efficiency, and improving user experience.
G06T 17/00 - Modélisation tridimensionnelle [3D] pour infographie
G06F 16/535 - Filtrage basé sur des données supplémentaires, p.ex. sur des profils d'utilisateurs ou de groupes
G06F 16/58 - Recherche caractérisée par l’utilisation de métadonnées, p.ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
G06F 16/953 - Requêtes, p.ex. en utilisant des moteurs de recherche du Web
G06V 10/74 - Appariement de motifs d’image ou de vidéo; Mesures de proximité dans les espaces de caractéristiques
97.
METHOD, ELECTRONIC DEVICE, AND COMPUTER PROGRAM PRODUCT FOR SESSION SWITCHING
Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for session switching. The method includes: establishing a first session with a first terminal in response to a session request initiated by the first terminal. The method further includes: generating first response information to first request information from the first terminal. The method further includes: determining a first confidence level of the first response information; and determining, in response to the first confidence level being lower than a confidence level threshold, to switch the first session to a second session between the first terminal and a second terminal. The method for session switching according to embodiments of the present disclosure can provide a fast and satisfactory response to a request made by a user, thereby effectively satisfying the user requirements and significantly improving the user experience.
Approximating state vector sparsity for quantum computing operations. A recurrent model is trained to predict sparsity indexes (sparsity vector) for a quantum circuit and its subcircuits. The computational requirements of a knitting operation can be estimated or predicted more efficiently using the predicted sparsity indexes. Cutting operations and decisions can also be based on the predicted sparsity indexes.
Ransomware activity detection and data protection is implemented by a remote R2 storage array on an asynchronous remote data replication facility, on which data from a primary R1 storage array is replicated to the remote storage array. Write operations on storage volumes in a remote data replication group are collected in a capture cycle on the primary storage array, along with IO pattern metadata describing both read and write operations on the storage volumes. At the end of the capture cycle, the update and metadata is transmitted to the remote storage array. The remote storage array receives the update and metadata and temporarily stores the update prior to applying it to its copy of the storage volumes. Ransomware anomaly detection is implemented using the update and metadata, and if ransomware activity is detected, the data on the remote R2 storage array is protected, and the update is not applied.
Methods and systems for authenticating data processing systems throughout a distributed environment without user intervention are disclosed. To authenticate data processing systems without user intervention, a system may include a network core and one or more data processing systems. A previously established root of trust between the network core and a data processing system may be lost and the network core may attempt to re-authenticate the data processing system using historical telemetry data. The historical telemetry data may be previously provided to the network core by the data processing system prior to the loss of the root of trust. The network core may provide the data processing system with a security questionnaire based on the telemetry data and the data processing system may use similar telemetry data to respond to the security questionnaire. If the answers to the security questions are considered accurate, the data processing system may be re-authenticated.
brevets
