Correlation Power Analysis for SM4 based on EEMD, Permutation Entropy and Singular Spectrum Analysis

Signal-to-noise ratio of the power consumption curves collected during encryption has a greater impact on the bits of Secret key cracked and the efficiency of later analysis. Wavelet threshold noise reduction’s parameters are difficult to determine. Method based on EEMD and correlation coefficients is hard to adjust. Therefore, a noise reduction algorithm combining EEMD, Permutation Entropy and Singular Spectrum Analysis is proposed. The algorithm decomposes the original power consumption curves using EEMD to obtain Intrinsic Mode Function components, selects noisy IMF on the basis of correlation coefficient and PE, and then uses SSA to extract useful signals. Original power consumption curves, power consumption curves processed by EEMD and correlation coefficient, and the power consumption curves obtained by the method proposed in this paper are compared, and the correlation coefficient is increased by 37.11% and 26.47% respectively. The proportion of curves consumed increased by 77.5% and 25.8% respectively.