Invention Grant
- Patent Title: Applying machine learning techniques to discover security impacts of application programming interfaces
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Application No.: US15356536Application Date: 2016-11-18
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Publication No.: US10339320B2Publication Date: 2019-07-02
- Inventor: Kristofer A. Duer , John T. Peyton, Jr. , Babita Sharma , David E. Stewart , Jason N. Todd , Shu Wang
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: Yee & Associates, P.C.
- Agent Jeffrey LaBaw
- Main IPC: G06F21/57
- IPC: G06F21/57 ; G06N20/00 ; G06F21/62
Abstract:
A computer-implemented method includes obtaining, by a processor, existing security information for static application security testing (SAST). The method also includes using, by the processor, the existing security information to discover, by a machine capable of learning, new security information. The method also includes improving, by the processor, security of a computer using the new security information.
Public/Granted literature
- US20180144127A1 APPLYING MACHINE LEARNING TECHNIQUES TO DISCOVER SECURITY IMPACTS OF APPLICATION PROGRAMMING INTERFACES Public/Granted day:2018-05-24
Information query
