Abstract: An information handling system may receive, from a first sensor of the information handling system, first sensor data. The information handling system may receive, from a second sensor of the information handling system, second sensor data. Based, at least in part, on the first sensor data and the second sensor data, the information handling system may generate a plurality of security profiles for the information handling system. Based, at least in part, on the first sensor data and the second sensor data, the information handling system may apply a security profile of the plurality of security profiles to the information handling system.

Abstract: Embodiments of systems and methods are provided to enhance network security by providing secure, multi-path user authentication, while also providing a more convenient login experience to the user. In the present disclosure, a cloud-based user authentication and threat detection system is provided with an artificial intelligence (AI) engine and a training dataset. Utilizing a cloud-based system enables the AI engine to collect data from multiple devices located within different physical locations or environments (such as, for example, the user's home and office). The collected data is stored within the training dataset and used to create a personalized user profile for each user. Each time a user initiates login to a system or network from a particular location, the AI engine collects data from multiple devices within that location and utilizes the user profile data previously stored within the training dataset to securely authenticate the user or detect potential security threats.

Abstract: A system and method for Embodiments of systems and methods for managing performance optimization of applications executed by an Information Handling System (IHS) are described. In an illustrative, non-limiting embodiment, an IHS may include computer-executable instructions to identify a current persona of a user of the IHS, identify an application that is associated with the current persona, and prioritize the application associated with the current persona. The current persona being one of multiple modes of operating the IHS by the user.

Abstract: An information handling system may predict, for a first time period, a first resource usage of a first information handling system resource for an application. The information handling system may also predict, for the first time period, a second resource usage level of a second information handling system resource different from the first information handling system resource for the application. The information handling system may adjust one or more performance parameters for the information handling system based on the first resource usage level and the second resource usage level.

Abstract: An information handling system (IHS) may receive, from a first sensor of the information handling system, first sensor data. The IHS may detect an individual other than a user of the IHS in a field of view of the first sensor based on the first sensor data. The IHS may then, in response to the first sensor detecting the individual, receive, from a second sensor of the IHS, second sensor data. Based, at least in part, on the first sensor data and the second sensor data, the IHS may determine relevance of the individual to an application displayed on a display of the IHS. The IHS may then generate an intent score for the individual based at least in part on the determined relevance. The IHS may then determine whether a security profile is to be applied to the IHS based, at least in part, on the intent score.

Abstract: The present disclosure provides various embodiments of systems and methods to securely authenticate a user. More specifically, the present disclosure provides embodiments of multi-factor authentication methods that improve both security and user convenience by using trusted secondary devices or peripherals (hereinafter “trusted devices”) to provide additional authentication factor(s) for verifying user presence/identity after an initial authentication factor has been used to verify user presence/identity. Unlike conventional multi-factor authentication methods, the additional authentication factor(s) provided by the trusted devices do not require user input or intervention.

Abstract: Embodiments of systems and methods are provided to enhance network security by providing secure, multi-path user authentication, while also providing a more convenient login experience to the user. In the present disclosure, a cloud-based user authentication and threat detection system is provided with an artificial intelligence (AI) engine and a training dataset. Utilizing a cloud-based system enables the AI engine to collect data from multiple devices located within different physical locations or environments (such as, for example, the user's home and office). The collected data is stored within the training dataset and used to create a personalized user profile for each user. Each time a user initiates login to a system or network from a particular location, the AI engine collects data from multiple devices within that location and utilizes the user profile data previously stored within the training dataset to securely authenticate the user or detect potential security threats.

Abstract: An information handling system presents audio information as audible sounds that include noise cancellation generated in response to environmental noise patterns detected by a microphone. For example, a machine learning model generates noise cancellation for plural environmental noise patterns, such as a baby crying, a dog barking, and a door bell ringing. The noise cancellation engine selectively applies and disables one or more types noise cancellation with the model based upon context at the information handling system, such as an application running on the system, a time of day or other factors.

Abstract: The present disclosure provides various embodiments of systems and methods to securely authenticate a user. More specifically, the present disclosure provides embodiments of multi-factor authentication methods that improve both security and user convenience by using trusted secondary devices or peripherals (hereinafter “trusted devices”) to provide additional authentication factor(s) for verifying user presence/identity after an initial authentication factor has been used to verify user presence/identity. Unlike conventional multi-factor authentication methods, the additional authentication factor(s) provided by the trusted devices do not require user input or intervention.

Abstract: User responsiveness on an information handling system may be improved by classifying an application based on its importance and/or relevance for an individual user with the goal of prioritizing resource allocation to improve responsiveness and performance of applications. The classification may include analyzing telemetry data to determine the most important applications for a user, such as by determining an application's importance and/or relevance to a particular user, and determine the resource utilization of that application from a macro perspective. After classification, changing characteristics of an application may be monitored and used to dynamically allocate system resources to the application during runtime. In this manner, priority on resource allocations for certain resources may be adapted to fit the user and the application, and adapt to the changing requirements and scenarios.

Abstract: Embodiments of systems and methods for managing performance optimization of applications executed by an Information Handling System (IHS) are described. In an illustrative, non-limiting embodiment, an IHS may include computer-executable instructions for determining one or more resource performance features of a resource used by the IHS using a first machine learning (ML) service, and determining one or more application performance features of a target application executed by the resource using a second ML service. Using the determined resource performance features and the application performance features, the instructions may generate a profile recommendation for the target application, and adjust one or more settings of the resource to optimize a performance of the target application executed by the resource.

Abstract: An information handling system may receive, from a first sensor of the information handling system, first sensor data. The information handling system may receive, from a second sensor of the information handling system, second sensor data. Based, at least in part, on the first sensor data and the second sensor data, the information handling system may generate a plurality of security profiles for the information handling system. Based, at least in part, on the first sensor data and the second sensor data, the information handling system may apply a security profile of the plurality of security profiles to the information handling system.