%0 Journal Article
%A DUAN Xiao-yi
%A HUANG Ke-zhen
%A LI Bing
%A YANG Dan
%A MA Xiang-liang
%T Reverse-Analysis of S-Box for SM4-Like Algorithms Based on Side Channel Technology
%D 
%R 10.13190/j.jbupt.2020-034
%J Journal of Beijing University of Posts and Telecommunications
%P 118-124
%V 43
%N 5
%X In the profiled scenario, the common method of reverse analysis is the template attack based on multi-Gaussian distribution. The article applies the concept of deep learning to the field of reverse analysis for the first time under the same conditions, and proposes an S-box reverse analysis algorithm based on deep learning. By selecting the deep learning algorithm, loss function and label design method suitable for side channel reverse analysis, an S-box reverse recovery experiment is conducted for SM4-like algorithm. It is shown that it is feasible to employ deep learning method to carry out S-box reverse analysis, which can have better performance comparing to template attack under certain circumstances. Moreover, the predicting effect of multi-layer perception algorithm surpasses that of convolutional neural network algorithm.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2020-034