Exploring Genomic Sequence Alignment for Improving Side Channel Analysis
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Side channel analysis (SCA) extracts sensitive information from a device by analyzing information that is leaked through side channels. These measurements are correlated with specific operations executed on the device (for example, encryption or decryption), allowing to extract useful information from the data. Countermeasures, however, disrupt the synchronization between the device’s operations and the corresponding side channel data, yielding their alignment a prerequisite for successful SCA.
In this work, we describe parallels between side channel analysis and molecular biology and propose a novel approach to align side channel traces using genomic sequence alignment methods. We find that Multiple Sequence Alignment techniques can align power traces with higher quality than elastic alignment (based on Dynamic Time Warping), thereby enabling downstream SCA methods (for example, Correlation Power Analysis) to extract cryptography keys with up to 44% less traces.