Name
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. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1186/s42400-020-00055-5 | Cybersecurity |
Keywords | DocType | Volume |
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 | Journal | 3 |
Issue | ISSN | Citations |
1 | 2523-3246 | 0 |
PageRank | References | Authors |
0.34 | 48 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Choi Yoon-Ho | 1 | 0 | 0.34 |
| Liu Peng | 2 | 0 | 0.34 |
| Shang Zitong | 3 | 0 | 0.34 |
| Wang Haizhou | 4 | 0 | 0.34 |
| Wang Zhilong | 5 | 0 | 0.34 |
| Zhang Lan | 6 | 0 | 0.34 |
| Junwei Zhou | 7 | 118 | 16.64 |
| Zou Qingtian | 8 | 0 | 0.34 |