Paul Nguyen

Paul Nguyen

Applied AI Engineer — Safety-Critical AI Products | Building Autodidact (local-first agent that learns) | PhD (Adversarial ML & Security)

A Novel Golden-Chip-Free Clustering Technique Using Backscattering Side Channel for Hardware Trojan Detection

Published in 2019 IEEE International Symposium on Hardware Oriented Security and Trust (HOST), 2020

🏆 Best Paper Award

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This paper presents a golden-chip-free approach to hardware trojan detection using electromagnetic backscattering side channels. Unlike traditional methods that require a known-good reference chip for comparison, our clustering technique can identify trojaned chips from a mixed population without any trusted reference — making it practical for real-world supply chain security where golden chips may not be available.

The work extends our earlier backscattering side-channel technique (IEEE TVLSI 2019) into a fully unsupervised detection framework, removing the strongest assumption in the hardware trojan detection literature.

Recommended citation: Luong N. Nguyen, Baki Berkay, Milos Prvulovic, and Alenka Zajic, "A Novel Golden-Chip-Free Clustering Technique Using Backscattering Side Channel for Hardware Trojan Detection," 2019 IEEE International Symposium on Hardware Oriented Security and Trust (HOST), Dec. 2020.