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CRC-Based Hardware Trojan Detection for Improved Hardware Security

Publication Type : Journal Article

Publisher : Lecture Notes in Electrical Engineering

Source : Lecture Notes in Electrical Engineering, Springer Verlag, Volume 471, p.381-389 (2018)

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041797772&doi=10.1007%2f978-981-10-7329-8_39&partnerID=40&md5=9c792520bae5a7bdb3494f65bf015460

ISBN : 9789811073281

Keywords : Detection accuracy, Detection efficiency, Gold, Golden reference, Hardware, hardware security, Hardware Trojan detection, Infrared imaging, Initial weights, Malicious activities, malware, Microelectronics, Pre-processing, Voting algorithm

Campus : Coimbatore

School : School of Engineering

Center : Electronics Communication and Instrumentation Forum (ECIF)

Department : Electronics and Communication

Year : 2018

Abstract : Several methodologies aim at tackling the issue of Hardware Trojans through the help of a “Golden Reference”, which is not always available; thereby arises the need for an efficient method without a Golden Reference. This work involves the detection of Hardware Trojan in a circuit using an improved voting algorithm employing CRC. Two modifications to a conventional voting algorithm are proposed in this chapter along with CRC to improve the detection efficiency. This logic-based detection procedure avoids the requirements of complex pre-processing procedures like segmentation, fingerprinting, thermal imaging, etc., The following proposed modifications (i) incapacitates the bias toward 1s and incorporating CRC for comparison of bit streams and (ii) equal weight of 1 is given as initial weight to all CUTs, which gives better results in voting algorithm. Detection accuracy is found to be around 95.27% based on the detailed analysis with infected and non-infected ISCAS’85 and ISCAS’89 circuits.

Cite this Research Publication : N Mohankumar, Dr. Jayakumar M., and M. Devi, N., “CRC-Based Hardware Trojan Detection for Improved Hardware Security”, Lecture Notes in Electrical Engineering, vol. 471, pp. 381-389, 2018.

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