Using deep learning to solve computer security challenges: a survey

Cybersecurity

article

Choi, Yoon-Ho¹  Liu, Peng¹  Shang, Zitong¹  Wang, Haizhou¹  Wang, Zhilong¹  Zhang, Lan¹  Zhou, Junwei³  Zou, Qingtian¹ 

[1] The Pennsylvania State University;Pusan National University;Wuhan University of Technology

关键词: 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;   

DOI  :  10.1186/s42400-020-00055-5

学科分类：社会科学、人文和艺术（综合）

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY