Paper 2017/1217

Linear Regression Side Channel Attack Applied on Constant XOR

Shan Fu, Zongyue Wang, Fanxing Wei, Guoai Xu, and An Wang

Abstract

Linear regression side channel attack (LRA) used to be known as a robust attacking method as it makes use of independent bits leakage. This leakage assumption is more general than Hamming weight/ Hamming distance model used in correlation power attack (CPA). However, in practice, Hamming weight and Hamming distance model suit most devices well. In this paper, we restudy linear regression attack under Hamming weight/ Hamming distance model and propose our novel LRA methods. We find that in many common scenarios LRA is not only an alternative but also a more efficient tool compared with CPA. Two typical cases are recovering keys with XOR operation leakage and chosen plaintext attack on block ciphers with leakages from round output. Simulation results are given to compare with traditional CPA in both cases. Our LRA method achieves up to 400% and 300% improvements for corresponding case compared with CPA respectively. Experiments with AES on SAKURA-G board also prove the efficiency of our methods in practice where 128 key bits are recovered with 1500 traces using XOR operation leakage and one key byte is recovered with only 50 chosen-plaintext traces in the other case.