Using Deep Learning to Solve Computer Security Challenges: A Survey
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.
Cite
@article{arxiv.1912.05721,
title = {Using Deep Learning to Solve Computer Security Challenges: A Survey},
author = {Yoon-Ho Choi and Peng Liu and Zitong Shang and Haizhou Wang and Zhilong Wang and Lan Zhang and Junwei Zhou and Qingtian Zou},
journal= {arXiv preprint arXiv:1912.05721},
year = {2021}
}
Comments
43 pages with 7 figures and two tables