Invention Grant
- Patent Title: Methods and systems for on-device high-granularity classification of device behaviors using multi-label models
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Application No.: US14837936Application Date: 2015-08-27
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Publication No.: US09910984B2Publication Date: 2018-03-06
- Inventor: Andres Valencia , Vinay Sridhara , Yin Chen , Rajarshi Gupta
- Applicant: QUALCOMM Incorporated
- Applicant Address: US CA San Diego
- Assignee: QUALCOMM Incorporated
- Current Assignee: QUALCOMM Incorporated
- Current Assignee Address: US CA San Diego
- Agency: The Marbury Law Group, PLLC
- Main IPC: G06F21/55
- IPC: G06F21/55 ; G06F21/57 ; G06N99/00 ; G06F21/56

Abstract:
Various aspects include methods and computing devices implementing the methods for evaluating device behaviors in the computing devices. Aspect methods may include using a behavior-based machine learning technique to classify a device behavior as one of benign, suspicious, and non-benign. Aspect methods may include using one of a multi-label classification and a meta-classification technique to sub-classify the device behavior into one or more sub-categories. Aspect methods may include determining a relative importance of the device behavior based on the sub-classification, and determining whether to perform robust behavior-based operations based on the determined relative importance of the device behavior.
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