Name
Title | ||
|---|---|---|
Evaluation of the Complexity of Automated Trace Alignment using Novel Power Obfuscation Methods. |
Abstract | ||
|---|---|---|
This paper presents a methodology for evaluating power obfuscation approaches that seek to obfuscate the location of sensitive operations in the power trace, thereby increasing the complexity of automated trace alignment. The paper presents a new adversary model and proposes a new metric, mean trials to success (MTTS), to evaluate power obfuscation methods in the context of automated trace alignment. We evaluate two common obfuscation methods, namely instruction shuffling and random instruction insertion, and we present a new obfuscation method using power shaping to intentionally mislead the attacker.
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Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3194554.3194640 | ACM Great Lakes Symposium on VLSI |
Keywords | Field | DocType |
Power obfuscation, power shaping, automated trace alignment, side channel attacks, embedded systems | Computer science,Adversary model,Real-time computing,Shuffling,Side channel attack,Obfuscation,Computer engineering | Conference |
ISSN | ISBN | Citations |
1066-1395 | 978-1-4503-5724-1 | 0 |
PageRank | References | Authors |
0.34 | 5 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bozhi Liu | 1 | 0 | 1.35 |
| Kemeng Chen | 2 | 0 | 1.01 |
| Minjun Seo | 3 | 7 | 2.94 |
| Janet Meiling Wang | 4 | 118 | 14.10 |
| Roman Lysecky | 5 | 605 | 60.43 |