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.
Original language | English (US) |
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Article number | 15 |
Journal | Cybersecurity |
Volume | 3 |
Issue number | 1 |
DOIs | |
State | Published - Dec 1 2020 |
Externally published | Yes |
Keywords
- Control-flow integrity
- Deep learning
- Fuzzing for software security
- Malware classification
- Memory forensics
- Network attacks
- Return-oriented programming attacks
- Security-oriented program analysis
- System-event-based anomaly detection
ASJC Scopus subject areas
- Software
- Information Systems
- Computer Networks and Communications
- Artificial Intelligence