Title
Side-Channel Attacks Based on Collaborative Learning.
Abstract
Side-channel attacks based on supervised learning require that the attacker have complete control over the cryptographic device and obtain a large number of labeled power traces. However, in real life, this requirement is usually not met. In this paper, an attack algorithm based on collaborative learning is proposed. The algorithm only needs to use a small number of labeled power traces to cooperate with the unlabeled power trace to realize the attack to cryptographic device. By experimenting with the DPA contest V4 dataset, the results show that the algorithm can improve the accuracy by about 20% compared with the pure supervised learning in the case of using only 10 labeled power traces.
Year
DOI
Venue
2017
10.1007/978-981-10-6385-5_46
Communications in Computer and Information Science
Keywords
DocType
Volume
Side-channel attacks,Supervised learning,Collaborative learning,Power trace
Conference
727
ISSN
Citations 
PageRank 
1865-0929
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Biao Liu156.54
Zhao Ding200.34
Yang Pan300.34
Jiali Li4499.29
Huamin Feng513414.65