Using deep learning to solve computer security challenges:a survey

查看全文 作　　者：Yoon-Ho [1,2]Choi;Peng [1]Liu;Zitong [1]Shang;Haizhou [1]Wang;Zhilong [1]Wang;Lan [1]Zhang;Junwei [3]Zhou;Qingtian [1]Zou 机构地区：[1]The Pennsylvania State University,Pennsylvania,USA;[2]Pusan National University,Busan,Republic of Korea;[3]Wuhan University of Technology,Wuhan,China 出　　处：《Cybersecurity》索引2018年第1卷第1期,共32页 基　　金：supported by ARO W911NF-13-1-0421(MURI),NSF CNS-1814679,and ARO W911NF-15-1-0576. 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. 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