Abstract: Methods, apparatus, systems and articles of manufacture to identify a side-channel attack are disclosed. Example instructions cause one or more processors to generate an event vector based on one or more counts corresponding to tasks performed by a central processing unit; determine distances between the event vector and weight vectors of neurons in a self-organizing map; select a neuron of the neurons that results based on a determined distance; identify neurons that neighbor the selected neuron; and update at least one of a weight vector of the selected neuron or weight vectors of the neighboring neurons based on the determined distance of the selected neuron.

Abstract: A system and method of dynamically controlling a reservation of resources within a cluster environment to maximize a response time are disclosed. The method embodiment of the invention includes receiving from a requestor a request for a reservation of resources in the cluster environment, reserving a first group of resources, evaluating resources within the cluster environment to determine if the response time can be improved and if the response time can be improved, then canceling the reservation for the first group of resources and reserving a second group of resources to process the request at the improved response time.

Abstract: Implementations detailed herein include description of a computer-implemented method.

Abstract: Disclosed system specifies, based on measurement results of communication times taken for accessing a plurality of external databases, relation between the communication times taken for accessing the plurality of external databases, calculates, when accepting an instruction to execute processing using at least one of the plurality of external databases, a processing load when accessing the at least one of the external databases, based on the relation between the communication times, and controls an access to data included in the at least one of the external databases according to the calculated processing load.

Abstract: A method of restoring an image of a computer, including identifying, by a backup application executing on the computer, artifacts of the computer to back up, creating a mirror image of a hard drive of the computer, wherein the mirror image comprises the artifacts, establishing a local environment within the computer, communicating with a backup server, by the backup application, using the local environment in the computer, backing up the mirror image, by the backup application, to the backup server using the local environment, updating the mirror image, by the backup application, in the backup server in response to a change in the computer, constructing the local environment on the computer in response to an event, loading a program from the local environment, and restoring the computer, by the backup application, from the mirror image in the backup server based on the artifacts, the program, and the restore process.

Abstract: Data protection for container storage, including: assigning, to a container storage volume of a storage system, a volume-level access policy; and determining whether to allow access to the container storage volume based on the volume-level access policy and one or more attributes of a request for the access, including allowing the access responsive to the one or more attributes meeting the volume-level access policy or denying the access responsive to the one or more attributes failing to meet the volume-level access policy.

Abstract: Disclosed herein are an apparatus, non-transitory computer readable medium, and method for querying big data and displaying the results of the query. A multilevel hierarchy of data structures is associated with a particular date to reduce the linearity of the search. The client receiving the query results stores the results in a linked list with a record format consistent with the resulting records. The client also periodically refreshes a graphical user interface with the query results until all the results are received.

Abstract: Techniques for providing batch performance using a stream processor are described. In one technique, a method includes receiving an event that includes an event key and a timestamp. The method then generates a partition value and time bucket value, the partition value generated based on the event key and the time bucket value generated based on the timestamp. The event key, partition value, and time bucket value are then combined to form a database key and used in a command to a database.

Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for AI based privacy amplification. A data security system allows for data transmitted between devices to be secured using varying levels of data security that are adjusted dynamically based on the determined sensitivity level of the data. The data security system uses AI (e.g., machine learning models) to predict the sensitivity level of data being transmitted between the devices in real-time and applies an appropriate level of data security based on the predicted sensitivity level. Dynamically adjusting the level of data security that is used based on the sensitivity level of the data provides for heightened levels of data security to protect highly sensitive data, and lower levels of data security to conserve computing resources when protecting less sensitive data.

Abstract: Systems and methods for blurring connection information in virtual private networks are provided herein. In some embodiments, a method of blurring VPN connection metadata may comprise: receiving, by a VPN service provider infrastructure, a request from a user device to establish a VPN connection with one or more VPN servers, wherein the VPN service provider infrastructure includes a logic engine configured to perform statistical blurring of VPN connection metadata; establishing a connection between the user device and one or more target sites during a VPN session; receiving, from the one or more VPN servers, VPN connection metadata associated with the user's VPN connections and a user identifier associated with the user; performing statistical blurring of VPN connection metadata by modifying the VPN connection metadata using an unknown random value to create blurred connection metadata; and storing the blurred connection metadata in association with the user identifier received.

Abstract: Provided with a technology of a machine learning using a convolutional neural network depending on practical calculation cost and security level desired by a user.

Abstract: In general, the invention relates to providing computer implemented services using information handling systems. One or more embodiments of the invention includes receiving a request to decompose a composed information handling system, wherein the composed information handling system comprises a hardware resource, obtaining a cleaning requirement for the hardware resource, initiating, based on the cleaning requirement, a cleaning operation on the hardware resource, receive a confirmation that the cleaning operation is complete, and after receiving the confirmation, set a state of the hardware resource to allocatable.

Abstract: A computer implemented method for distributing, collecting and monitoring assignments by a content management system. The method includes receiving a request for a file request from a teacher to distribute an assignment to one or more students. In response to receiving the request, the teacher is prompted for information associated with the assignment. The information can include a name for the assignment, an assignment file and a collection identifier. In response to receiving the information, one or more metadata tags are generated based on the received information. The file request is distributed along with the one or more metadata tags to the one or more student.

Abstract: Embodiments of the invention are directed to a method. The method may include transmitting, by a first device, an encrypted first biometric template generated from a first biometric sample of a user of the first device to a second device, wherein the second device inputs the encrypted first biometric template and a second biometric template generated from a second biometric sample of the user into a function to generate an encoded output. The first device may receive the encoded output from the second device, and may decode the encoded output to recover the encrypted first biometric template and the second biometric template of the user. Upon determining a match result between first and second biometric templates, the first device may transmit unique data to the second device.

Abstract: A prefetch mechanism stores data in the memory allocated in a remote passive (remote) node in a High Availability active-passive node pair. A read-ahead cache that can host different parts of a file is created on both the active and the passive nodes. The system improves the performance of sequential restores by using memory available on a passive node to supplement the local (active node) memory to hold the prefetched data for the common case of large sequential restores. This extra memory overcomes issues when a current prefetch fails to keep up with the target restore performance. Filesystem redirection is thus accomplished by servicing an I/O request by sending it another node that itself caches the data.

Abstract: An illustrative method includes receiving a request to create a storage volume; identifying, based on the request and on a configuration file propagated among a plurality of storage nodes in a cluster, status indicators of the storage nodes; identifying, based on the request, a size of the storage volume; identifying, based on the request, a replication factor representing a number of storage nodes that are to be replicated within a cluster for the storage volume; identifying, based on one or more characteristics associated with the storage volume, a traffic priority for the storage volume, the traffic priority representing a hierarchy that determines and prioritizes which traffic is allocated to available hardware and network resources in a particular order; creating, based on the status indicators, the size, the replication factor, and the traffic priority, the storage volume on one or more of the plurality of storage nodes.

Abstract: This document discloses a system and method for securing data files selected from a series of data files. The system comprises a transformation module, an artificial neural network (ANN), a clustering module and a backpropagation module whereby these modules are configured to identify data files that contain malware or anomalies. When such data files are detected, the system will then initiate a series of measures to identify other data files that may be similarly afflicted by the detected malware. These data files are then secured to prevent the malware from affecting a host machine and/or any storage/peripheral devices linked to the host machine.

Abstract: Systems, apparatuses, methods, and computer program products are disclosed for managing open issues. An example method includes obtaining a dashboard access request for a portion of open issues managed by the issue management system, the issue management system storing variables associated with each open issue of the open issues; obtaining a dashboard data package based on scores for the portion of open issues, the scores indicating a severity level of the open issues of the portion of open issues and being based on the variables that are stored in the issue management system; and performing an action set using the dashboard data package to manage the portion of open issues.

Abstract: Disclosed is a dynamic network risk predicting method based on a graph neural network, which comprises the following steps: collecting network data firstly and constructing a network data sequence graph; extracting the time sequence of the network data sequence graph and obtaining a time sequence feature graph; extracting network attribute features, network structure features and network change features of the dynamic network; obtaining the representation vector of the network sequence graph by learning the representation vector; constructing the anomaly detection model and carrying out the dynamic network risk prediction.

Abstract: A communication redundancy system for an autonomous vehicle includes: a vehicle network domain including a bus configured to transmit a signal, terminal end resistors disposed at both ends of the bus, and a plurality of electronic control units (ECUs) connected to the bus; a plurality of gateways connected to the vehicle network domain; and a high-level ECU connected to the plurality of gateways and configured to control the plurality of ECUs to implement autonomous driving of a vehicle. Each of the plurality of gateways detects disconnection of the bus in the vehicle network domain and, when the disconnection of the bus is detected, the plurality of gateways transmit pieces of data of the plurality of ECUs to the high-level ECU.