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ATTRITION: Attacking Static Hardware Trojan Detection Techniques Using Reinforcement Learning. (arXiv:2208.12897v1 [cs.CR])
Aug. 30, 2022, 1:20 a.m. | Vasudev Gohil, Hao Guo, Satwik Patnaik, Jeyavijayan (JV) Rajendran
cs.CR updates on arXiv.org arxiv.org
Stealthy hardware Trojans (HTs) inserted during the fabrication of integrated
circuits can bypass the security of critical infrastructures. Although
researchers have proposed many techniques to detect HTs, several limitations
exist, including: (i) a low success rate, (ii) high algorithmic complexity, and
(iii) a large number of test patterns. Furthermore, the most pertinent drawback
of prior detection techniques stems from an incorrect evaluation methodology,
i.e., they assume that an adversary inserts HTs randomly. Such inappropriate
adversarial assumptions enable detection techniques to …
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