Side Channel Analysis Based on Convolutional Auto-encoder

doi:10.3969/j.issn.1006-2475.2024.03.018

Abstract

Abstract: Abstract： As an important indicator in side channel analysis， Points-Of-Interest （POI） is of great significance to accurately select effective POI. Aiming at the problem of poor selection of POI in the clustering model of public key cryptography algorithm， which leads to low recognition rate， this paper proposes a method of POI selection based on convolutional auto-encoder. After data preprocessing， the method uses convolutional auto-encoder to learn data features， and uses its encoded output as the selected POI， combines with clustering algorithm to complete side channel attack， and finally successfully recoveres the key. The experiment takes the multi-point operation process in the SM2 decryption algorithm as the research object， and the results show that the proposed method can be used for data POI selection in the side channel analysis， which greatly improves the flexibility and practicality of neural networks in side channel analysis.

Key words: Key words： side channel, convolutional auto-encoder, clustering, SM2 algorithm, POI selection

CLC Number:

TP309

ZENG Zhong-jing-xin, GAN Gang. Side Channel Analysis Based on Convolutional Auto-encoder[J]. Computer and Modernization, 2024, 0(03): 110-114.

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