Name
Title | ||
|---|---|---|
Profiled Power-Analysis Attacks by an Efficient Architectural Extension of a CNN Implementation |
Abstract | ||
|---|---|---|
In a recent line of works, several masking and unmasking AES design have been proposed to secure hardware implementations against power-analysis techniques. Although Machine-learning profiling techniques have been successful in security testing during the last years, evaluation of hardware security still requires improvement because of the growing complexity of leakage models against profiled side... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ISQED51717.2021.9424361 | 2021 22nd International Symposium on Quality Electronic Design (ISQED) |
Keywords | DocType | ISSN |
Measurement,Power demand,Neural networks,Side-channel attacks,Machine learning,Hardware,Libraries | Conference | 1948-3287 |
ISBN | Citations | PageRank |
978-1-7281-7641-3 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Soroor Ghandali | 1 | 0 | 0.34 |
| Samaneh Ghandali | 2 | 0 | 0.34 |
| Sara Tehranipoor | 3 | 0 | 0.34 |