Locating Vulnerability in Binaries Using Deep Neural Networks

Binary fault localization is important for vulnerability analysis, but many current techniques face problems in locating vulnerability accurately and effectively, especially for real-world programs. In this paper, we propose a novel gradient-guided vulnerability locating method named DeepVL, which l...

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Bibliographic Details

Published in:	IEEE Access
Main Authors:	Runhao Li, Chen Zhang, Chao Feng, Xing Zhang, Chaojing Tang
Format:	Article
Language:	English
Published:	IEEE 2019-01-01
Subjects:	Binary program crash deep learning execution trace fault localization neural networks software security
Online Access:	https://ieeexplore.ieee.org/document/8843873/