Improving non-profiled attacks on exponentiations based on clustering and extracting leakage from multi-channel high-resolution EM measurements

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Abstract

The success probability of side-channel attacks depends on the used measurement techniques as well as the algorithmic processing to exploit available leakage. This is particularly critical in case of asymmetric cryptography, where attackers are only allowed single side-channel observations because secrets are either ephemeral or blinded by countermeasures. We focus on non-profiled attacks which require less attacker privileges and cannot be prevented easily. We significantly improve the algorithmic processing in non-profiled attacks based on clustering against exponentiation-based implementations compared to previous contributions. This improvement is mainly due to PCA and a strategy to select few mid-ranked components where exploitable, low-variance leakage is concentrated. As a result from a practical experiment using single-channel high-resolution magnetic field measurements, we report a significant improvement in the number of successful attacks. Further, we present the first practical results from using three such channels simultaneously. The combination of three channels leads to further improved results over the best individual channel when applying a profiled template attack. The clustering-based algorithmic approach for the non-profiled attack, however, does not show improvements from the combination.

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APA

Specht, R., Heyszl, J., Kleinsteuber, M., & Sigl, G. (2015). Improving non-profiled attacks on exponentiations based on clustering and extracting leakage from multi-channel high-resolution EM measurements. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9064, pp. 3–19). Springer Verlag. https://doi.org/10.1007/978-3-319-21476-4_1

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