Trojan localization using symbolic algebra
Farimah Farahmandi, Yuanwen Huang, Prabhat Mishra · 2017
Growing reliance on reusable hardware Intellectual Property (IP) blocks, severely affects the security and trustworthiness of System-on-Chips (SoCs) since untrusted third-party vendors may deliberately insert malicious components to incorporate undesired functionality. Malicious implants may also work as hidden backdoor and leak protected information. In this paper, we propose an automated approach to identify untrustworthy IPs and localize malicious functional modifications (if any). The technique is based on extracting polynomials from gate-level implementation of the untrustworthy IP and comparing them with specification polynomials. The proposed approach is applicable when the specification is available. Our approach is scalable due to manipulation of polynomials instead of BDD-based analysis used in traditional equivalence checking techniques. Experimental results using Trust-HUB benchmarks demonstrate that our approach improves both localization and test generation efficiency by several orders of magnitude compared to the state-of-the-art Trojan detection techniques.