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In essence, side-channel leakages produced during the execution of crypto implementations are noisy physical measurements. It turns out that various noises contained in leakages have, in general, negative effects on the key-recovery efficiency of side-channel attacks. Therefore, in practice, frequency-based denoising methods are presented and in wide use nowadays. However, most of them for reducing noises of high-frequency are not always effective, and they sometimes do little or even no help. On the other hand, the relationship between noises extracted with different denoising methods that target different frequencies, in time-domain, is not being discussed, which in turn will determine the potential power of combining these denoising methods. Motivated by this, we present two empirical mode decomposition (EMD) based denoising methods for side-channel attacks, and study their effectiveness in reducing noises of high frequency in real power traces. Compared with their counterparts, EMD-based denoising methods achieve both effectiveness and stability. Furthermore, we investigate the relationships between the noises extracted with denoising methods that target different frequencies, by performing attacks on real power traces denoised by multiple combinations of different denoising methods. For this purpose, we define the notion of overlapping coefficient, which measures how much that noises are overlapped with each other. Our results and observations are evidently verified by correlation power analysis attacks on multiple real power traces sets.

EMD-Based Denoising for Side-Channel Attacks and Relationships between the Noises Extracted with Different Denoising Methods