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Titlebook: Constructive Side-Channel Analysis and Secure Design; 15th International W Romain Wacquez,Naofumi Homma Conference proceedings 2024 The Edi

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書目名稱Constructive Side-Channel Analysis and Secure Design
副標(biāo)題15th International W
編輯Romain Wacquez,Naofumi Homma
視頻videohttp://file.papertrans.cn/237/236124/236124.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Constructive Side-Channel Analysis and Secure Design; 15th International W Romain Wacquez,Naofumi Homma Conference proceedings 2024 The Edi
描述.This book constitutes the refereed proceedings of the 15th International Workshop on Constructive Side-Channel Analysis and Secure Design, COSADE 2024, held in ?Gardanne, France, during April 9–10, 2024.?..The 14 full papers included in this book were carefully reviewed and selected from?42?submissions. They were organized in topical sections as follows:?Analyses and Tools;?Attack Methods;?Deep-Learning-Based Side-Channel Attacks;?PUF/RNG; and?Cryptographic Implementations..
出版日期Conference proceedings 2024
關(guān)鍵詞artificial intelligence; authentication; computer hardware; computer networks; computer science; computer
版次1
doihttps://doi.org/10.1007/978-3-031-57543-3
isbn_softcover978-3-031-57542-6
isbn_ebook978-3-031-57543-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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978-3-031-57542-6The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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Rui Chen,Dehui Li,Qihua Xiong,Handong Suning faults into target circuits. These days, EMFI draws attention as a real threat to cryptographic circuits because of its inherent advantages. Although EMFI has become popular, there are only a few works on EMFI at the lowest physical level. In this paper, we experimentally show that EMFI induces
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https://doi.org/10.1007/978-3-642-28018-4s pointed out a significant challenge: overcoming the initial learning plateau. This paper discusses the advantages of multi-task learning to break through the initial plateau consistently. We investigate different ways of applying multi-task learning against masked AES implementations (via the ASCA
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