Name
Abstract | ||
|---|---|---|
This article approaches to design an attack-aware detection and defense framework to resist adversarial attacks on the security-critical artificial intelligent systems. We first make efforts to test the performances of adversarial attacks and present classifying and grading rule (CGR) for the fine-grained grouping of adversarial example attacks. According to CGR, adversarial attacks can be divided... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TCAD.2020.3033746 | IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems |
Keywords | DocType | Volume |
Perturbation methods,Feature extraction,Detectors,Neural networks,Resists,Security,Computational modeling | Journal | 40 |
Issue | ISSN | Citations |
10 | 0278-0070 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei Jiang | 1 | 3 | 4.13 |
| Zhiyuan He | 2 | 2 | 1.73 |
| Jinyu Zhan | 3 | 3 | 8.15 |
| Weijia Pan | 4 | 0 | 0.68 |