earticle

영어

To overcome the dependence on prior knowledge of traditional filtering algorithm, this paper proposes a novel non-parameter and adaptive multivariate empirical mode decomposition interval threshold (MEMD-IT) denoising approach for signal preprocessing of electromagnetic template attack(ETA). MEMD-IT can reduce the discontinuity induced by traditional MEMD-DT and aims to remove the Gaussian noise coupled into side-channel electromagnetic radiations. The proposed method and some other filters such as butterworth low-pass filter(BLPF)，wavelet threshold denoising and MEMD direct threshold (MEMD-DT) denoising are applied to analyze the electromagnetic radiation traces intercepted while cipher device was implementing RC4 encryption algorithm. Furthermore, twin SVM multi-class classifier based ETA was performed to evaluate the attack results. In the same attack scenario, the highest predictive success rate for 9 Hamming Weights of the key reached 92%,90%,84%,83% and 73% for MEMD-IT, WFTF, MEMD-DT,WULETF and BLPF preprocessing methods, respectively. The experiment results indicate that our proposed scheme has a significant performance compared with the traditional ETA.