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TrojanWhisper: Evaluating Pre-trained LLMs to Detect and Localize Hardware Trojans
Md Omar Faruque, Peter Jamieson, Ahmad Patooghy +1
Existing Hardware Trojans (HT) detection methods face several critical limitations: logic testing struggles with scalability and coverage for large designs, side-channel analysis r…
Unleashing GHOST: An LLM-Powered Framework for Automated Hardware Trojan Design
Md Omar Faruque, Peter Jamieson, Ahmad Patooghy +1
Traditionally, inserting realistic Hardware Trojans (HTs) into complex hardware systems has been a time-consuming and manual process, requiring comprehensive knowledge of the desig…
TrojanForge: Generating Adversarial Hardware Trojan Examples Using Reinforcement Learning
Amin Sarihi, Peter Jamieson, Ahmad Patooghy +1
The Hardware Trojan (HT) problem can be thought of as a continuous game between attackers and defenders, each striving to outsmart the other by leveraging any available means for a…
The Seeker's Dilemma: Realistic Formulation and Benchmarking for Hardware Trojan Detection
Amin Sarihi, Ahmad Patooghy, Abdel-Hameed A. Badawy +1
This work focuses on advancing security research in the hardware design space by formally defining the realistic problem of Hardware Trojan (HT) detection. The goal is to model HT…