Newness and distinctiveness is claimed in the features of ornamentation as shown inside the broken line circle in the accompanying representation.

Display screen or portion thereof with graphical user interface

In embodiments of the present invention improved capabilities are described for managing digital rights management (DRM) protected content sharing in a networked secure collaborative computer data exchange environment through a secure exchange facility managed by an intermediate organizational entity amongst users of a plurality of other organizational entities, wherein computer data content and access rights for the computer data content is shared between a first and second user, the computer data content and access rights for the computer data content are transformed into a DRM protected computer data content through communications with a DRM engine, wherein the DRM engine is selected based on a content type of the computer data content, and the DRM engine is provided by an entity other than the intermediate organizational entity and other than any of the plurality of other organizational entities.

Systems and methods of secure data exchange

Methods, devices and systems for detecting suspicious or performance-degrading mobile device behaviors intelligently, dynamically, and/or adaptively determine computing device behaviors that are to be observed, the number of behaviors that are to be observed, and the level of detail or granularity at which the mobile device behaviors are to be observed. The various aspects efficiently identify suspicious or performance-degrading mobile device behaviors without requiring an excessive amount of processing, memory, or energy resources.

Adaptive Observation of Behavioral Features on a Mobile Device

Methods, systems and devices for generating data models in a client-cloud communication system may include applying machine learning techniques to generate a first family of classifier models that describe a cloud corpus of behavior vectors. Such vectors may be analyzed to identify factors in the first family of classifier models that have the highest probability of enabling a mobile device to better determine whether a mobile device behavior is malicious or benign. Based on this analysis, a second family of classifier models may be generated that identify significantly fewer factors and data points as being relevant for enabling the mobile device to better determine whether the mobile device behavior is malicious or benign based on the determined factors. A mobile device classifier module based on the second family of classifier models may be generated and made available for download by mobile devices, including devices contributing behavior vectors.

On-line behavioral analysis engine in mobile device with multiple analyzer model providers

The present disclosure provides a system that includes a server hosting an application under test (AUT), an observer configured to monitor instructions executed by the AUT, and a computing device communicatively coupled to the AUT and the observer through a common communication channel. The computing device may be configured to send an application request to the AUT, wherein the application request is configured to expose a potential vulnerability of the AUT. The computing device may receive an application response from the AUT in accordance with the AUT's programming. The computing device may send a service request to the observer, and receive a service response from the observer that contains information corresponding to the instructions executed by the AUT due to the application request, information about the AUT, or information about a server hosting the AUT.

Application security testing

A system is disclosed that includes components and features for enabling enterprise users to securely access enterprise resources (documents, data, application servers, etc.) using their mobile devices. An enterprise can use some or all components of the system to, for example, securely but flexibly implement a BYOD (bring your own device) policy in which users can run both personal applications and secure enterprise applications on their mobile devices. The system may, for example, implement policies for controlling mobile device accesses to enterprise resources based on device attributes (e.g., what mobile applications are installed), user attributes (e.g., the user's position or department), behavioral attributes, and other criteria. Client-side code installed on the mobile devices may further enhance security by, for example, creating a secure container for locally storing enterprise data, creating a secure execution environment for running enterprise applications, and/or creating secure application tunnels for communicating with the enterprise system.

Olivier Andre

Papers

Secure execution of enterprise applications on mobile devices

Secure container for protecting enterprise data on a mobile device

Secure mobile browser for protecting enterprise data

Modifying pre-existing mobile applications to implement enterprise security policies

Controlling mobile device access to enterprise resources