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- W2116787154 abstract "Side channel attacks take advantage of information leakages in cryptographic devices. Template attacks form a family of side channel attacks which is reputed to be extremely effective. This kind of attacks assumes that the attacker fully controls a cryptographic device before attacking a similar one. In this paper, we propose to relax this assumption by generalizing the template attack using a method based on a semi-supervised learning strategy. The effectiveness of our proposal is confirmed by software simulations, by experiments on a 8-bit microcontroller and by a comparison to a template attack as well as to two supervised machine learning methods." @default.
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- W2116787154 date "2013-01-01" @default.
- W2116787154 modified "2023-10-12" @default.
- W2116787154 title "Semi-Supervised Template Attack" @default.
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- W2116787154 doi "https://doi.org/10.1007/978-3-642-40026-1_12" @default.
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