Binary code vulnerability detection is an important research issue. Aiming at the problems of high false alarm rate, coarse detection granularity and dependence on expert experience in current binary code vulnerability detection system based on static analysis, this paper proposes to use library/API function call program slice to represent binary program with fine granularity, and introduces deep learning technology to automatically detect the related vulnerabilities in library/API function call of binary program. A deep learning-based method is designed and implemented. Binary code vulnerability detection system - BVDetector. By analyzing the control flow and data flow of binary program, the system extracts the program slices of library/API function calls from the program, and adds vulnerability labels to the program slices.

Filename	Size	Update
基于深度学习的二进制代码漏洞检测系统.pdf	1004878	2019-04-12

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