CRAINov 11, 2024

X-DFS: Explainable Artificial Intelligence Guided Design-for-Security Solution Space Exploration

arXiv:2411.07308v13 citationsh-index: 53IEEE Trans Inf Forensics Secur
Originality Incremental advance
AI Analysis

This work addresses security vulnerabilities in the semiconductor supply chain for hardware designers, offering a more efficient and interpretable method, though it appears incremental as it builds on existing DFS strategies with AI guidance.

The paper tackles the challenge of developing Design-for-Security (DFS) solutions for integrated circuits, which are often slow and lack human-understandable formalisms, by proposing X-DFS, an explainable AI-guided approach that reduces mitigation strategy development time by providing human-understandable rationales.

Design and manufacturing of integrated circuits predominantly use a globally distributed semiconductor supply chain involving diverse entities. The modern semiconductor supply chain has been designed to boost production efficiency, but is filled with major security concerns such as malicious modifications (hardware Trojans), reverse engineering (RE), and cloning. While being deployed, digital systems are also subject to a plethora of threats such as power, timing, and electromagnetic (EM) side channel attacks. Many Design-for-Security (DFS) solutions have been proposed to deal with these vulnerabilities, and such solutions (DFS) relays on strategic modifications (e.g., logic locking, side channel resilient masking, and dummy logic insertion) of the digital designs for ensuring a higher level of security. However, most of these DFS strategies lack robust formalism, are often not human-understandable, and require an extensive amount of human expert effort during their development/use. All of these factors make it difficult to keep up with the ever growing number of microelectronic vulnerabilities. In this work, we propose X-DFS, an explainable Artificial Intelligence (AI) guided DFS solution-space exploration approach that can dramatically cut down the mitigation strategy development/use time while enriching our understanding of the vulnerability by providing human-understandable decision rationale. We implement X-DFS and comprehensively evaluate it for reverse engineering threats (SAIL, SWEEP, and OMLA) and formalize a generalized mechanism for applying X-DFS to defend against other threats such as hardware Trojans, fault attacks, and side channel attacks for seamless future extensions.

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