Name
Abstract | ||
|---|---|---|
Recently, it was shown that the generative adversarial network (GAN) based adversarial-example attacks could thoroughly defeat the existing Android malware detection systems. However, they can be easily defended through deploying a firewall (i.e., adversarial example detector) to filter adversarial examples. To evade both malware detection and adversarial example detection, we develop a new advers... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/JSYST.2019.2906120 | IEEE Systems Journal |
Keywords | DocType | Volume |
Malware,Gallium nitride,Generators,Detectors,Feature extraction,Training,Generative adversarial networks | Journal | 14 |
Issue | ISSN | Citations |
1 | 1932-8184 | 5 |
PageRank | References | Authors |
0.45 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Heng Li | 1 | 325 | 33.39 |
| ShiYao Zhou | 2 | 6 | 0.81 |
| Wei Yuan | 3 | 145 | 11.94 |
| Jiahuan Li | 4 | 5 | 0.45 |
| Henry Leung | 5 | 1309 | 151.88 |