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Improve the Performance of SemiSupervised Side-channel Analysis Using HWFilter Method

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成果类型:
期刊论文
作者:
Zhang, Hong;Li, Lang;Li, Di
通讯作者:
Li, L
作者机构:
[Zhang, Hong; Li, Lang; Li, Di] Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang 421002, Peoples R China.
[Zhang, Hong; Li, Lang; Li, Di] Hengyang Normal Univ, Hunan Prov Key Lab Intelligent Informat Proc & App, Hengyang 421002, Peoples R China.
通讯机构:
[Li, L ] H
Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang 421002, Peoples R China.
Hengyang Normal Univ, Hunan Prov Key Lab Intelligent Informat Proc & App, Hengyang 421002, Peoples R China.
语种:
英文
关键词:
Learning systems;Side channel attack;Analysis models;Cryptanalytic techniques;Hamming weights;Normal distribution.;Performance;Power traces;Pseudo-label filter;Semi-supervised;Semi-supervised learning;Side-channel analysis;Normal distribution
期刊:
KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS
ISSN:
1976-7277
年:
2024
卷:
18
期:
3
页码:
738-754
基金类别:
Hunan Provincial Natural Science Foundation of China [2022JJ30103]; Science and Technology Innovation Program of Hunan Province [2016TP1020]; The 14th Five-Year Plan" Key Disciplines and Application oriented Special Disciplines of Hunan Province [xiangjiaotong [2022] 351]; Open fund project of Hunan Provincial Key Laboratory of Intelligent Information Processing and Application for Hengyang Normal University [2022HSKFJJ011]
机构署名:
本校为第一且通讯机构
院系归属:
计算机科学与技术学院
物理与电子工程学院
摘要:
Side-channel analysis (SCA) is a cryptanalytic technique that exploits physical leakages, such as power consumption or electromagnetic emanations, from cryptographic devices to extract secret keys used in cryptographic algorithms. Recent studies have shown that training SCA models with semi-supervised learning can effectively overcome the problem of few labeled power traces. However, the process of training SCA models using semi-supervised learning generates many pseudo-labels. The performance of the SCA model can be reduced by some of these ps...

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