Name
Title | ||
|---|---|---|
Bias Busters: Robustifying DL-Based Lithographic Hotspot Detectors Against Backdooring Attacks |
Abstract | ||
|---|---|---|
Deep learning (DL) offers potential improvements throughout the CAD tool-flow, one promising application being lithographic hotspot detection. However, DL techniques have been shown to be especially vulnerable to inference and training time adversarial attacks. Recent work has demonstrated that a small fraction of malicious physical designers can stealthily “backdoor” a DL-based hotspot detector d... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TCAD.2020.3033749 | IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems |
Keywords | DocType | Volume |
Training,Training data,Layout,Robustness,Detectors,Solid modeling,Lithography | Journal | 40 |
Issue | ISSN | Citations |
10 | 0278-0070 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kang Liu | 1 | 52 | 7.60 |
| Benjamin Tan | 2 | 5 | 3.58 |
| Reddy Gaurav Rajavendra | 3 | 0 | 0.34 |
| Siddharth Garg | 4 | 675 | 55.14 |
| Makris, Y. | 5 | 20 | 7.02 |
| Ramesh Karri | 6 | 2968 | 224.90 |