Abstract
Hardware Trojan detection has emerged as a critical challenge to ensure security and trustworthiness of integrated circuits. A vast majority of research efforts in this area has utilized side-channel analysis for Trojan detection. Functional test generation for logic testing is a promising alternative but it may not be helpful if a Trojan cannot be fully activated or the Trojan effect cannot be propagated to the observable outputs. Side-channel analysis, on the other hand, can achieve significantly higher detection coverage for Trojans of all types/sizes, since it does not require activation/propagation of an unknown Trojan. However, they have often limited effectiveness due to poor detection sensitivity under large process variations and small Trojan footprint in side-channel signature. In this chapter, we address this critical problem through a novel side-channel-aware test generation approach, based on a concept of multiple excitation of rare switching (MERS) that can significantly increase Trojan detection sensitivity. (1) It presents in detail a scalable statistical test generation method, which can generate high-quality testset for creating high relative activity in arbitrary Trojan instances; (2) it analyzes the effectiveness of generated testset in terms of Trojan coverage; and (3) it describes two judicious reordering methods that can further tune the testset and greatly improve the side-channel sensitivity. Simulation results demonstrate that the tests generated by MERS can significantly increase the Trojans sensitivity, thereby making Trojan detection effective using side-channel analysis.
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Notes
- 1.
We have performed structural partitioning [15] with partition factor p = 50%, which generally achieves better SCS than a skewed partition. If the designer can afford the cost, different partition factor p can be explored.
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Farahmandi, F., Huang, Y., Mishra, P. (2020). Trojan Detection Using Dynamic Current Analysis. In: System-on-Chip Security. Springer, Cham. https://doi.org/10.1007/978-3-030-30596-3_10
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DOI: https://doi.org/10.1007/978-3-030-30596-3_10
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