A Hardware Trojan Detection Method Based on Compression Marginal Fisher Analysis

Xiaohan WANG; Tao WANG; Xiongwei LI; Yang ZHANG; Changyang HUANG

doi:10.11999/JEIT190004

Volume 41 Issue 12

Dec. 2019

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Article Navigation > Journal of Electronics & Information Technology > 2019 > 41(12): 3043-3050

Xiaohan WANG, Tao WANG, Xiongwei LI, Yang ZHANG, Changyang HUANG. A Hardware Trojan Detection Method Based on Compression Marginal Fisher Analysis[J]. Journal of Electronics & Information Technology, 2019, 41(12): 3043-3050. doi: 10.11999/JEIT190004

Citation:

Xiaohan WANG, Tao WANG, Xiongwei LI, Yang ZHANG, Changyang HUANG. A Hardware Trojan Detection Method Based on Compression Marginal Fisher Analysis[J]. Journal of Electronics & Information Technology, 2019, 41(12): 3043-3050. doi: 10.11999/JEIT190004

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A Hardware Trojan Detection Method Based on Compression Marginal Fisher Analysis

doi: 10.11999/JEIT190004

Equipment Simulation Training Center, Army Engineering University Shijiazhuang Campus, Shijiazhuang 050003, China

Funds: The National Natural Science Foundation of China (61602505)

Received Date: 2019-01-03
Rev Recd Date: 2019-03-14

Available Online: 2019-05-28

Publish Date: 2019-12-01

Abstract

Abstract

Against the problem of low detection rate to detect small hardware Trojan by side-channel in physical environment, the Marginal Fisher Analysis (MFA) is introduced. On the basis, a hardware Trojan detection method based on Compression Marginal Fisher Analysis (CMFA) is proposed. The projection space is constructed by reducing the distance between the sample and its same neighbor samples, and the distance between the same neighbor samples and the center of the same kind, and increasing the distance between the same neighbor samples of the center and the sample in different kind. Thus, the difference in the original data is found without any assumptions about data distribution, and the detection of hardware Trojan is achieved. The hardware Trojan detection experiment in AES encryption circuit shows that this method can effectively distinguish the statistical difference in side-channel signal between reference chip and Trojan chip and detect the hardware Trojan whose scale is 0.04% of the original circuit.
- Hardware Trojan detection,
- Integrated Circuit(IC),
- Side-channel analysis,
- Manifold learning,
- Marginal Fisher Analysis (MFA)

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References(17)

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