Although using machine learning techniques to solve computer security
challenges is not a new idea, the rapidly emerging Deep Learning technology has
recently triggered a substantial amount of interests in the computer security
community. This paper seeks to provide a dedicated review of the very recent
research works on using Deep Learning techniques to solve computer security
challenges. In particular, the review covers eight computer security problems
being solved by applications of Deep Learning: security-oriented program
analysis, defending return-oriented programming (ROP) attacks, achieving
control-flow integrity (CFI), defending network attacks, malware
classification, system-event-based anomaly detection, memory forensics, and
fuzzing for software security.

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Author Of this post: <a href="">Yoon-Ho Choi</a>, <a href="">Peng Liu</a>, <a href="">Zitong Shang</a>, <a href="">Haizhou Wang</a>, <a href="">Zhilong Wang</a>, <a href="">Lan Zhang</a>, <a href="">Junwei Zhou</a>, <a href="">Qingtian Zou</a>

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