Presentation | 2021-02-05 Hardware Trojan Detection by Learning Power Side Channel Signals Considering Random Process Variation Michiko Inoue, Riaz-Ul-Haque Mian, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Due to the globalization and complexity of the supply chain, there is a growing concern about the insertion of hardware Trojan circuits into semiconductor integrated circuits. In this paper, we propose a method to detect hardware Trojan circuits by learning side-channel signals. The method uses a power Monte Carlo simulation with random process variation annotated delay information. We propose a method to learn the dynamic power variation due to delay variation and to detectthe abnormal power value caused by hardware Trojan circuits. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | hardware Trojan circuit / random process variation / power analysis / outlier detection |
Paper # | DC2020-70 |
Date of Issue | 2021-01-29 (DC) |
Conference Information | |
Committee | DC |
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Conference Date | 2021/2/5(1days) |
Place (in Japanese) | (See Japanese page) |
Place (in English) | Online |
Topics (in Japanese) | (See Japanese page) |
Topics (in English) | |
Chair | Hiroshi Takahashi(Ehime Univ.) |
Vice Chair | Tatsuhiro Tsuchiya(Osaka Univ.) |
Secretary | Tatsuhiro Tsuchiya(Nihon Univ.) |
Assistant |
Paper Information | |
Registration To | Technical Committee on Dependable Computing |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Hardware Trojan Detection by Learning Power Side Channel Signals Considering Random Process Variation |
Sub Title (in English) | |
Keyword(1) | hardware Trojan circuit |
Keyword(2) | random process variation |
Keyword(3) | power analysis |
Keyword(4) | outlier detection |
1st Author's Name | Michiko Inoue |
1st Author's Affiliation | Nara Institute of Science and Technology(NAIST) |
2nd Author's Name | Riaz-Ul-Haque Mian |
2nd Author's Affiliation | Nara Institute of Science and Technology(NAIST) |
Date | 2021-02-05 |
Paper # | DC2020-70 |
Volume (vol) | vol.120 |
Number (no) | DC-358 |
Page | pp.pp.7-11(DC), |
#Pages | 5 |
Date of Issue | 2021-01-29 (DC) |