Method and system for efficient classification of mobile device behavior using application-specific and application-type-specific models

Abstract

Methods and mobile devices implementing the methods use application-specific and / or application-type-specific classifiers to improve the efficiency and performance of a comprehensive behavior monitoring and analysis system that predicts whether a software application is causing undesired behavior or performance degradation Behavior. Application-specific and application-type-specific classifier models may include a reduced and more focused subset of decision nodes included in a full classifier model or a more complete classifier model that may be received or generated in the mobile device. Locally generated application-specific and / or application-type-specific classifier models may be applied to behavior / feature vectors generated by monitoring mobile device behavior, using these application-based classifier models to perform real-time behavior monitoring and analysis operations. Aspects focus on monitoring and analyzing operations on a small number of features that are most important for determining whether operation of a software application contributes to undesired or performance-degrading behavior.

Description

[0001] related application [0002] This application claims priority to U.S. Provisional Application No. 61 / 912,624, filed December 6, 2013, entitled "Methods and Systems of Using Application-Specific and Application-Type-Specific Models for the Efficient Classification of Mobile Device Behaviors" interest, the entire content of this application is hereby incorporated by reference. Background technique [0003] Cellular and wireless communication technologies have experienced explosive growth in the last few years. This growth is fueled by better communications, hardware, larger networks, and more reliable protocols. As a result, wireless service providers are now able to provide their customers with unprecedented levels of access to information, resources and communications. [0004] To keep pace with these service enhancements, mobile electronic devices (eg, cellular phones, tablet devices, laptop computers, etc.) have become more powerful and complex than in the past. Th...

AI Technical Summary

Problems solved by technology

[0004] To keep pace with these service enhancements, mobile electronic devices (e.g., cellular phones, tablet devices, laptop computers, etc.) have become more powerful and complex than in the past

This complexity creates new opportunities for malware, software conflicts, hardware failures, and other similar errors or phenomena that negatively impact the long-term sustained performance and power utilization levels of mobile devices

Images