Lookout, Inc.

Samuel Alexander Walker

Brian James Buck

Kevin Patrick Mahaffey

David Luke Richardson

Ayan Kanti Mandal

David Golombek

Ariel Salomon

Devesh Senapati

R Tyler Croy

Sergio Ivan Marcin Gorrino

User activity on a mobile device is monitored and collected, and a resource usage model is constructed. The resource usage model describes a set of contexts in which the mobile device, and is the basis for determining a first exhaustion point for a resource. Based on the monitored activity, a prediction of a second exhaustion point for the resource time is made. If the second exhaustion point is prior to the first exhaustion point, usage of the resource is reduced.

System and method for using context models to control operation of a mobile communications device

Embodiments are directed to a system and method for authenticating a user of a client computer making a request to a server computer providing access to a network resource through an authentication platform that issues a challenge in response to the request requiring authentication of the user identity through a reply from the client computer, determining one or more items of context information related to at least one of the user, the request, and the client computer, and determining a disposition of the request based on the reply and the one or more items of context information. The reply includes a user password and may be provided by an authorizing client device.

Multi-factor authentication and comprehensive login system for client-server networks

Security is enhanced for a user of a mobile device by monitoring and controlling resource usage. Usage information associated with a mobile device is collected. The collected information is used to build a usage model for a user of the mobile device that describes a set of contexts in which the mobile device is used. User activity on the device is monitored and the model is consulted to determine a first time after which it will be acceptable for a battery of the mobile device to fall below a threshold charge level. Based on the monitored activity, a prediction of a second time is made for when the battery will fall below the threshold charge level. If the second time is before or a predetermined amount of time before the first time, usage of the battery is reduced, else, usage of the battery is not reduced.

System and method for developing, updating, and using user device behavioral context models to modify user, device, and application state, settings and behavior for enhanced user security

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Littleton, CO, United States of America

Samuel Alexander Walker