Machine-Learning-Based Multiple Abstraction-Level Detection of Hardware Trojan Inserted at Register-Transfer Level
Hardware Trojan refers to a malicious modification of an integrated circuit (IC). To eliminate the complications arising from designing an IC which includes a Trojan, it is suggested to apply Trojan detection as early as at register-transfer level (RTL). In this paper, we propose a hardware Trojan d...
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| Main Authors: | , , , , , , , |
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| Format: | Conference or Workshop Item |
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IEEE Computer Society
2019
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078343218&doi=10.1109%2fATS47505.2019.00018&partnerID=40&md5=c5da625563674630028625dd473f86be http://eprints.utp.edu.my/23662/ |
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| Summary: | Hardware Trojan refers to a malicious modification of an integrated circuit (IC). To eliminate the complications arising from designing an IC which includes a Trojan, it is suggested to apply Trojan detection as early as at register-transfer level (RTL). In this paper, we propose a hardware Trojan detection framework which consists of both RTL and gate-level classification using machine learning approaches to detect hardware Trojan inserted at RTL. In the experiment, all Trojan benchmarks were successfully identified without false positive detection on non-Trojan benchmark. © 2019 IEEE. |
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