Abstract: Metadata about files present at clients is collected. The metadata includes values for a set of features associated with the files. The values are normalized and centroids are calculated. For each file, a comparison is performed of a normalized value of a feature associated with a file against a respective centroid calculated for the feature. Based on the comparison, the file is or is not backed up. A machine learning model is applied to files that have been backed up to tier the backed up files.

Abstract: Values corresponding to a set of features associated with each file of a set of files are collected. The features include an access frequency, modification time, sensitivity level, retention priority, and file type. The values are normalized and centroids are calculated. Normalized values and corresponding centroids of features of the files are compared. The files are tiered based on the comparison.

Abstract: A method for managing a data protection system includes monitoring, by an interaction manager, a data protection workload executing on the data protection system, wherein the data protection system comprises a plurality of services, and wherein the data protection workload is executed by the plurality of services communicating with each other using application programming interface (API) calls, obtaining, based on the monitoring, a copy of the API calls, performing an embedding on the copy of the API calls to obtain API embeddings, applying the API embeddings to a failure prediction engine to obtain a failure prediction for the data protection workload, performing a remediation action on the API calls to remediate the data protection workload, and updating the failure prediction engine based on the remediation action.

Abstract: A method for managing a data protection system includes obtaining, by an interaction manager, a failure notification for a data protection workload executing on the data protection system, wherein the data protection system comprises a plurality of services, and wherein the data protection workload is executed by the plurality of services communicating with each other using application programming interface (API) calls, based on the failure notification, identifying a portion of the plurality of services used for the data protection workload, performing a recreation of the data protection workload to identify a failure point associated with the failure notification, and performing a remediation action of the data protection workload based on the recreation.

Abstract: A method for managing a data protection system includes monitoring, by an interaction manager, a data protection workload executing on the data protection system, wherein the data protection workload is executed by a plurality of services communicating with each other using application programming interface (API) calls, obtaining a copy of the API calls, detecting a failure associated with the data protection workload using the copy of the API calls, performing a root cause analysis on the failure using historical API calls of the data protection system and based on a random forest machine learning algorithm and a support vector machine algorithm, performing a remediation action based on the root cause analysis and using a failure prediction engine, and updating an action-reward associated with the remediation action and applying a reinforcement learning on the failure prediction engine based on the action-reward to obtain an updated failure prediction engine.

Abstract: The present disclosure relates to a system (300) for providing route guidance using augmented reality, the system includes a processor (502) to obtain a set of orientation parameters of a subject (304) based on one or more sensors accommodated in a computing device (302) associated with the subject and determine one or more motion parameters associated with the subject to reach the destination from a target location. The processor generates a set of arrows indicating at least one direction of the path from the target location of the subject to the destination, wherein when the set of orientation parameters deviates from the one or more motion parameters, the processor configured to calculate a degree of rotation to align the set of arrows indicating the at least one direction of the path along the desired direction to reach the destination to facilitate route guidance.

Abstract: A method for managing a data protection system includes obtaining, by an interaction manager, a historical dataset of a plurality of application programming interface (API) calls from the data protection system for a plurality of data protection workloads, wherein each of the plurality of data protection workloads is executed by the plurality of services communicating with each other using the API calls, in response to obtaining the historical datasets, identifying a portion of the plurality of services used for each of the plurality of data protection workloads, generating a set of synthetic workloads based on the historical dataset and based on the identifying, wherein the set of synthetic workloads are generated using generative adversarial networks (GANs), performing a simulation of the set of synthetic workloads to obtain traffic statistics, and performing a preventive action of the data protection system based on the simulation and using the traffic statistics.

Abstract: A method for managing a data protection system includes obtaining, by an interaction manager, a set of historical application programming interface (API) calls between a plurality of services for a data protection workload in the data protection system, wherein the data protection workload is executed by a plurality of services communicating with each other using the historical API calls, identifying a portion of the plurality of services used for the data protection workload, performing a subsystem health evaluation on each of the portion of the plurality of services based on the set of historical API calls to obtain a reliability score for each service, performing a system evaluation of the data protection system based on the reliability score of each of the portion of the plurality of services, and performing a preventive action on the data protection system based on the system evaluation.

Abstract: A data protection system uses machine learning to detect the cyber-attacks on a data protection system in advance to notify the user of possible attacks and also instigate any counter attacks to the best possible extent. The system trains a support vector machine model (SVM) to recognize a malware, or other type of attack before it comes into action against the system. This model learns the parameters of hazardous files or code to prepare the best model of attributes of such files to help block the malware proactively. It uses several independent variables as features to gain more accuracy to the threat detection. Some of the parameters include: rate of data change (Drastic/High/Low), attack vulnerability history, resource usage history, performance metrics, application hit ratio, and the like.

Abstract: A method for managing a data protection system includes obtaining, by an interaction manager, a failure notification for a data protection workload executing on the data protection system, wherein the data protection system comprises a plurality of services, and wherein the data protection workload is executed by the plurality of services communicating with each other using application programming interface (API) calls, based on the failure notification, identifying a portion of the plurality of services used for the data protection workload, performing a recreation of the data protection workload to identify a failure point associated with the failure notification, and performing a remediation action of the data protection workload based on the recreation.

Abstract: Various embodiments of the technology described herein programmatically expand the capabilities of computing systems to allow for the determination of a host authority value indicative of a reliability of a particular host identified as a node in a Host Navigation Graph (HNG). A classifier or other neural network model is trained, based on the HNG, to classify or determine a reliability the particular host based on the host authority value. Based on the host authority value, the particular host is classified and a mitigation is taken to reduce the negative effects associated with a user interacting with a low-authority host. An example mitigation action includes generating a graphical user interface (GUI) element to notify a user of the reliability of a particular host, for example, before, during, or after a user interacts with the host.

Abstract: A system can use a first model to produce a first output that indicates a prediction of a mass handover event in a broadband cellular network. The system can use a second model to produce a second output that classifies respective user equipment of a group of user equipment according to a criticality criterion. The system can, based on the first output and the second output, adjust a centralized unit-decentralized unit mapping applicable to network equipment of the broadband cellular network to satisfy a network load balance criterion corresponding to maintaining at least a threshold network load balance and to satisfy a power usage criterion corresponding to maintaining at most a threshold power usage, to produce an adjusted centralized unit-decentralized unit mapping. The system can conduct broadband cellular communications via the network equipment according to the adjusted centralized unit-decentralized unit mapping.

Abstract: An apparatus comprises at least one processing device configured to identify statistical personally identifiable information (PII) variables in a dataset and to determine, for each of the statistical PII variables, a sensitivity level characterizing a contribution of that statistical PII variable in revealing individual user identities in the dataset. The at least one processing device is further configured to select, for each of the statistical PII variables, a masking level to be applied to that statistical PII variable based at least in part on the determined sensitivity level for that statistical PII variable. The at least one processing device is further configured to anonymize the dataset by applying selective masking to respective ones of the statistical PII variables in accordance with selected masking levels. The at least one processing device is further configured to perform one or more analytics operations in an information technology infrastructure utilizing the anonymized dataset.

Abstract: An exemplary method of displaying an intraoperative image of a surgical site comprises: receiving a plurality of images captured by a plurality of in-light cameras integrated into one or more surgical light units illuminating the surgical site, wherein the plurality of images capture the surgical site from a plurality of different perspectives; identifying an obstruction to the surgical site in an image of the plurality of images; responsive to identifying the obstruction, generating a composite image based on a set of the plurality of images, wherein the composite image excludes the obstruction; and displaying the composite image as the intraoperative image of the surgical site.

Abstract: Techniques described herein relate to a method for performing threat simulations. The method includes preparing a multi-cloud infrastructure (MCI) for live data collection, wherein: the MCI includes components, a first component of the components is associated with a first cloud service provider, and a second component of the components is associated with a second cloud service provider; obtaining, after the preparing, live data from the MCI; generating a prediction using the live data and a prediction model, wherein the prediction specifies whether the live data indicates that there is a threat within the MCI; making a first determination that the prediction indicates a threat associated with the MCI has been identified; and in response to the first determination: performing threat remediation using the prediction and a diagnostic repository.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for extracting and tracing ridges at junctions, including confluences, corners, and terminals. For example, the disclosed systems generate, from a digital image, a pixel ridge using a distance transform and a depth-first traversal of pixels in the digital image. In some embodiments, the disclosed systems determine a junction within the pixel ridge by segmenting the pixel ridge into logical branches. In certain embodiments, the disclosed systems classify the junction as a confluence based on determining that the junction is made up of at least a threshold number of incident branches within the pixel ridge. In some embodiments, the disclosed systems reconstruct the confluence by detecting a region of deformity for the confluence and replacing pixels in the region of deformity with extrapolated pixels connecting incident branches.

Abstract: Embodiments of a device and method are disclosed. In an embodiment, a method of communications involves at a wireless sensor deployed at a customer site, associating with a wireless access point (AP) using a fixed service set identifier (SSID), at the wireless sensor, transmitting an authentication request to an authentication server through the wireless AP, where the authentication request contains a certificate that is stored in the wireless sensor, and at the wireless sensor, receiving an authentication response from the authentication server through the wireless AP in response to the authentication request.

Abstract: Embodiments of a device and method are disclosed. In an embodiment, a method of communications involves at a cloud authentication server, receiving an authentication request of a wireless sensor deployed at a customer site through a wireless access point (AP) to which the wireless sensor is associated, where the authentication request contains a certificate that is stored in the wireless sensor, at the cloud authentication server, performing an authentication operation to determine whether a tenant corresponding to the certificate matches a tenant corresponding to the wireless AP to which the wireless sensor is associated, and at the cloud authentication server, transmitting an authentication response to the wireless sensor through the wireless AP in response to the authentication operation.

Abstract: A system can maintain a group of priority queues for messages, wherein respective existing messages are assigned to respective priority queues of the group of priority queues based on a first policy. The system can change from the first policy to a second policy with respect to the group of priority queues, wherein the changing is performed independently of disrupting delivery of the existing messages. The system can assign respective new messages to the respective priority queues based on the second policy. The system can, based on changing to the second policy, re-order the respective existing messages of the respective priority queues from respective rears of the respective priority queues to respective fronts of the respective priority queues. The system can deliver at least some of the respective existing messages and at least some of the respective new messages from the respective priority queues.

Abstract: A system can receive a group of data packets originated by at least one edge device. The system can decrypt respective data packets of the group of data packets, to reconstruct a file that is represented by the group of data packets. The system can extract a contextual value of the file. The system can input the respective contextual values and a defined rulebook to a retrieval-augmented generation system, wherein the defined rulebook comprises rules applicable to traffic routing in a human-readable format, and wherein the retrieval-augmented generation system outputs a priority for transmission of the group of data packets. The system can transmit the group of data packets to a destination based on the priority and the defined rulebook.