Using Deep Learning to Solve Computer Security Challenges: A Survey
December 12, 2019 ยท The Cartographer ยท ๐ Cybersecurity
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Authors
Yoon-Ho Choi, Peng Liu, Zitong Shang, Haizhou Wang, Zhilong Wang, Lan Zhang, Junwei Zhou, Qingtian Zou
arXiv ID
1912.05721
Category
cs.CR: Cryptography & Security
Citations
35
Venue
Cybersecurity
Last Checked
2 days ago
Abstract
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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