14 citations · 18 across the 5 of their papers we have counts for
5 papers
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…
Trojan Playground: A Reinforcement Learning Framework for Hardware Trojan Insertion and Detection
Amin Sarihi, Ahmad Patooghy, Peter Jamieson +1
Current Hardware Trojan (HT) detection techniques are mostly developed based on a limited set of HT benchmarks. Existing HT benchmark circuits are generated with multiple shortcomi…
Multi-criteria Hardware Trojan Detection: A Reinforcement Learning Approach
Amin Sarihi, Peter Jamieson, Ahmad Patooghy +1
Hardware Trojans (HTs) are undesired design or manufacturing modifications that can severely alter the security and functionality of digital integrated circuits. HTs can be inserte…
Hardware Trojan Insertion Using Reinforcement Learning
Amin Sarihi, Ahmad Patooghy, Peter Jamieson +1
This paper utilizes Reinforcement Learning (RL) as a means to automate the Hardware Trojan (HT) insertion process to eliminate the inherent human biases that limit the development…