Abstract
Preprocessing is a very important step in side channel analysis. The quality of the collected power traces seriously affects the efficiency of side channel analysis. Therefore, the preprocessing of Wavelet Transform (WT) and Wavelet Packet Denoising (WPD) are widely used. However, WT has certain defects in characterizing detail information of power traces. The threshold of WPD is not universal and adaptive. In order to solve these problems, it provides a preprocessing of power traces by combining WPD and Singular Spectrum Analysis (SSA), which takes advantage of the former to resolve the power consumption data, and the latter is used to extract the information of the low frequency and high frequency parts. Then, according to the fluctuation trend of singular entropy, the key information contained in the two parts is extracted adaptively, so as to improve the quality of power traces. Finally, through the selection of plaintext attack on the SM4 algorithm implemented by hardware, it can improve the efficiency of Correlation Power Analysis (CPA).
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Acknowledgements
This work is supported by the National Key Research and Development Program of China Under Grants No. 2017YFB0802000, National Cryptography Development Fund of China Under Grants No. MMJJ20170112, the Natural Science Basic Research Plan in Shaanxi Province of china (Grant Nos. 2018JM6028), National Nature Science Foundation of China (Grant Nos. 61772550, 61572521, U1636114, 61402531), Engineering University of PAP’s Funding for Scientific Research Innovation Team (grant no. KYTD201805).
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Ma, P., Wang, Zy., Zhong, W., Wang, X.A. (2020). Preprocessing of Correlation Power Analysis Based on Improved Wavelet Packet. In: Barolli, L., Hellinckx, P., Natwichai, J. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing. 3PGCIC 2019. Lecture Notes in Networks and Systems, vol 96. Springer, Cham. https://doi.org/10.1007/978-3-030-33509-0_34
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DOI: https://doi.org/10.1007/978-3-030-33509-0_34
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