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Using deep learning to solve computer security challenges: a survey
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DOI：10.1186/s42400-020-00055-5.png)
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摘要
En 中文
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.
Keyword:
Deep learning
Security-oriented program analysis
Return-oriented programming attacks
Control-flow integrity
Network attacks
Malware classification
System-event-based anomaly detection
Memory forensics
Fuzzing for software security
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C
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3.7
论文数:
609
被引数:
1.0K
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