Abstract: Embodiments of systems and methods to provide a firmware update to devices configured in a redundant configuration in an Information Handling System (IHS) are disclosed. In an illustrative, non-limiting embodiment, an IHS may include computer-executable instructions to, when a signed certificate associated with a client expires, challenge the client by transmitting a first plurality of keys to a client IHS, wherein the client IHS is configured to respond the challenge by associating each of the keys with a second plurality of keys, pairing each of the first key with its associated second key, sending the paired first and second keys to the server IHS, and authenticate the client IHS by verifying that each of the first plurality of keys is associated with the second plurality of keys.

Abstract: A ransomware protection smart network interface controller (SmartNIC) is configured to create a secure snapshot of a boot device of an information handling system (IHS), create a secure alternate boot device on each boot of the IHS, and export the boot device and the secure alternate boot device to the IHS. The IHS is configured to set a boot order of the IHS, with the secure alternate boot device immediately after the boot device in the boot order. The ransomware protection SmartNIC may also be configured to create a read and writeable snapshot from the secure snapshot of the IHS boot device, and may delete, on each subsequent boot of the IHS, the read and writeable snapshot for the prior boot, and create a new read and writeable snapshot from a secure snapshot of the IHS boot device from the subsequent boot of the IHS.

Abstract: Systems and methods for enabling contextual privacy controls in heterogenous computing platforms are described. In a non-limiting embodiment, an Information Handling System (IHS) may include a heterogeneous computing platform having a plurality of devices and a memory coupled to the platform, the memory including a plurality of sets of firmware instructions that, upon execution by a respective device among the plurality of devices, enable the respective device to provide a corresponding firmware service, where at least one of the plurality of devices operates as an orchestrator configured to: execute or instruct a device to execute an Artificial Intelligence model usable to identify one of a plurality of privacy modes to be applied to the IHS based, at least in part, upon context data received from at least a subset of the plurality of devices; and, based upon the identified privacy mode, modify one or more IHS settings.

Abstract: A method may include, in response to a condition related to a particular device of a plurality of devices in an information handling system, causing a particular visual indicator associated with the particular device to illuminate in accordance with a blink pattern. The blink pattern may include one or more first durations of time in which the particular visual indicator is illuminated, one or more second durations of time significantly shorter than the first durations of time in which the particular visual indicator is illuminated, and a plurality of third durations of time significantly shorter than the first durations of time and the second durations of time in which the particular visual indicator is darkened, wherein each first duration of time occurs immediately before and after a third duration of time and each second duration of time occurs immediately before and after a third duration of time.

Abstract: Systems and methods for enabling localized image enhancements in heterogenous computing platforms are described. In an illustrative, non-limiting embodiment, an Information Handling System may include a heterogeneous computing platform having a plurality of devices and a memory coupled to the heterogeneous computing platform, where the memory includes a plurality of sets of firmware instructions, where each of the sets of firmware instructions, upon execution by a respective device among the plurality of devices, enables the respective device to provide a corresponding firmware service, and where at least one of the plurality of devices operates as an orchestrator configured to: receive context or telemetry data from a subset of one or more of the plurality of devices; and instruct a selected device among the plurality of devices to execute an Artificial Intelligence model configured to produce a localized image based, at least in part, upon the context or telemetry data.

Abstract: Systems and methods for detecting video gaming sessions in heterogenous computing platforms are described. In an illustrative, non-limiting embodiment, an Information Handling System (IHS) may include a heterogeneous computing platform comprising a plurality of devices and a memory coupled to the heterogeneous computing platform, where the memory comprises a plurality of sets of firmware instructions, where each of the sets of firmware instructions, upon execution by a respective device among the plurality of devices, enables the respective device to provide a corresponding firmware service, and where at least one of the plurality of devices operates as an orchestrator configured to: receive context or telemetry data from at least a subset of the plurality of devices, and instruct a device among the plurality of devices to execute an Artificial Intelligence (AI) model configured to detect a video gaming session based, at least in part, upon the context or telemetry data.

Abstract: Described methods and systems for achieving an optical bokeh effect by a camera supporting a computing device, such as a laptop computer. A measurement is performed as to focus spot position of a subject. The depth of field (DOF) of camera lens is determined. An offset as to the focus spot position is calculated such the background of the subject would be blurred to increase the optical bokeh effect. The offset is added to the focus spot position or to be more in focus to decrease optical bokeh in the background, to arrive at a focus spot position that supports the optical bokeh effect. The camera lens is adjusted for the new focus spot position.

Abstract: A ransomware protection smart network interface controller (SmartNIC) is configured to implement data protection in a domain of the SmartNIC by taking a secure snapshot, a point in time image of a storage object, and retaining the point in time image of the storage object until a retention timer has expired, and implementing vault semantics and operational controls. The ransomware protection SmartNIC is also configured to implement ransomware detection in the domain of the SmartNIC by implementing inline ransomware attack detection and/or near-line ransomware attack detection, using periodic snapshots, by evaluating probability of a ransomware attack based, at least in part, on a delta change set in consecutive snapshots. The ransomware protection SmartNIC is further configured to implement ransomware protection policies in the domain of the SmartNIC by implementing policies of when the secure snapshots are taken.

Abstract: Disclosed subject matter enables a recovery and resume of secure platform services based on indicator of attack for the UEFI boot path and UEFI drivers for any access to storage or network medium. Disclosed methods may employ an unsupervised learning model, based on information referred to herein as Indicator of Attack (IOA) information, and create a unique resilient BIOS access for UEFI drivers, file system, media and network. Disclosed teachings enable secure services for access to UEFI drivers, file systems, media, and network using a dynamic resilient layer to handle IOA. Dynamic methods to create runtime metadata for file system logical blocks for OEM nested file system partition and pre boot OEM authentication are also disclosed. Disclosed teachings support a UEFI file system interface that implements a runtime remap method for OEM-provided drivers.

Abstract: Described herein are methods and a system for to optimize utilization of rack space supporting components of an existing client site rack. Real time data as to the rack space is collected, along with an objective function as to expansion. Information as to an initial design configuration is retrieved. A reinforcement learning algorithm processes real time data, the objective function, and initial design configuration to determine a deployment recommendation.

Abstract: An information handling system mouse has a variable speed scroll wheel with magnetic tactile response. A ferromagnetic wheel coupled to the scroll wheel and having spikes and valleys interacts with a magnetic field of magnet as the scroll wheel rotates to resist rotation in variable amounts. The magnetic field is selectively removed to reduce the tactile response, such as by disengaging a magnet from a magnetic focus lens that directs the magnetic field, moving an opposing magnet into contact with the magnetic focus lens that cancels the magnetic field and moving the magnet away from the ferromagnetic wheel.

Abstract: Within a domain such as a data center, host server activity monitors running on storage nodes observe meaningful commands sent by host servers to the storage nodes. Inactivity indicated by failure of any of the activity monitors to receive a meaningful command from a host server within a predetermined time limit prompts generation of a message that identifies that host server as possibly being unused. The host server activity monitors are also configured to identify as a possible unused host server any host server that is zoned for at least one of the storage nodes but not masked to any storage objects. If a quiescent host server becomes active, as indicated by resumption of sending meaningful commands to one of the storage nodes, then a message warning of a potential malicious attack is generated.

Abstract: A system can migrate a source file system on a first computer to a destination file system on a second computer. The system can receive, at the second computer, a request from a client computer that indicates a file system operation, and that references a source file handle of the source file system that comprises an identifier of the source file system. The system can identify the destination file system based on the identifier of the source file system. The system can determine, from a source inode number of the source file handle, a source inode number segment. The system can determine, from the source inode number segment, a destination inode number segment. The system can determine, from the destination inode number segment, a destination inode number. The system can perform the file system operation on the destination file system using the destination inode number and the identifier of the destination file system.

Abstract: Presented are efficient systems and methods for automatically detecting and configuring network connections in Fibre Channel (FC) and similar networks. In various embodiments, this is accomplished by using an I/O module (IOM)'s fabric login (FLOGI) response or FLOGI request to identify the type of an uplink interface as either FC Gateway or FC Direct Attach, determining whether server interfaces coupled to the TOM support FCoE, and then, automatically configuring server interfaces based on the identified type of uplink interface.

Abstract: Techniques are provided for managing metadata of a storage system. A storage control system manages a storage metadata structure which comprises metadata items for accessing data items in a storage system comprising a persistent write cache and a primary storage. The storage metadata structure comprises a first metadata structure that is configured to organize metadata items received from the write cache at a first granularity, and a second metadata structure that is configured to organize metadata items received from the first metadata structure at a second granularity, wherein the second granularity is greater than the first granularity. The storage control system utilizes the storage metadata structure to access data items in the persistent write cache and the primary storage.

Abstract: A system, method, and computer-readable medium are disclosed for performing a data center monitoring and management operation. The data center monitoring and management operation includes: identifying data center asset data to monitor; collecting data center asset data; and, performing an adaptive update scheduling operation, the adaptive update scheduling operation adaptively adjusting a prioritization and frequency of data center asset data collection to provide adapted data center asset data.

Abstract: In one aspect, an example methodology implementing the disclosed techniques includes, by a computing device, retrieving touchpoint data of a product and creating a data element based on the retrieved touchpoint data, the data element includes information about a touchpoint of the product by a stakeholder. The method also includes, by the computing device, adding the created data element to a product pedigree list, wherein the product pedigree list is a pedigree list which contains data elements of the product. The method may further include, by the computing device, storing the product pedigree list in a graph database. The method may further include, by the computing device, predicting, using a machine learning (ML) model (e.g., an autoencoder), whether a state of the product pedigree list is normal or anomalous.

Abstract: A load balancing algorithm and cluster configuration details are stored at each of a set of namespace nodes of a cluster hosting a deduplicated file system. Upon a client connecting to a namespace node, a server-initiated communication channel is established between the namespace node and the client over which updates to the load balancing algorithm, cluster configuration details, or both are sent. The load balancing algorithm and cluster configuration details are sent to the client, thereby allowing the client to determine according to the load balancing algorithm and cluster configuration details, which particular namespace node should handle a particular file system operation. Thereafter, each connected client is immediately notified of changes to the cluster such as node or service additions or deletions or software upgrades to the cluster so that each client can use the updated information to conduct load balancing.

Abstract: Each node of a storage cluster determines its capabilities and advertises the set of capabilities along with respective capability weights to other nodes of the storage cluster. Nodes monitor their systems for capability changes and, as capabilities of the nodes dynamically change, the dynamic changes to the node capabilities are similarly advertised. The advertised capabilities are passed to a cluster service manager which creates capabilities groups based on the advertised capabilities of the nodes. When a service is deployed to the storage cluster or moved within the cluster, the cluster service manager determines the set of required capabilities associated with the service, and uses the capabilities groups to identify nodes of the storage cluster for implementation of the service. Where more than one node has advertised the required sets of capabilities, the weights are used in an election process to determine which node should be used to implement the service.

Abstract: Embodiments of the present disclosure relate to a computer-implemented method, device, and computer program product. The method includes: determining, based on a set of user behavior data over a first time period, a set of behavioral features for a user behavior over the first time period. The method further includes: determining, based on the set of behavioral features, a set of anomaly scores for the user behavior according to an anomaly detection model. The anomaly detection model is trained based on user behavior data over a second time period. The method further includes: updating a previously determined anomaly score threshold based on comparison of the determined set of anomaly scores with the anomaly score threshold. The anomaly score threshold is used for indicating whether the user behavior is anomalous. By continuously updating the anomaly score threshold, the solution uses the updated anomaly score threshold for anomaly detection of user behavior.