2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)
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Abstract

Hardware Trojan threats caused by malicious designers and untrusted manufacturers have become one of serious issues in modern VLSI systems. In this paper, we show some experimental results to insert hardware Trojans into asynchronous circuits. As a result, the overhead of hardware Trojan insertion in asynchronous circuits may be small for malicious designers who have enough knowledge about the asynchronous circuits. In addition, we also show several Trojan detection methods using deep learning schemes which have been proposed to detect synchronous hardware Trojan in the netlist level. We apply them to asynchronous hardware Trojan circuits and show their results. They have a great potential to detect a hardware Trojan in asynchronous circuits.
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Towards a Distributed Inference Detection System in a Multi-Database Context
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