Abstract
Collision attack is an effective method in the field of side-channel analysis to crack cryptographic algorithms, and masking can be used as a countermeasure. Most collision attacks only utilize the traces that will collide. In this paper, we propose a collision attack method that exploits not only traces tending to collide, but also non-colliding traces. It can bring higher efficiency and reduce the number of needed traces significantly. In addition, our method is a random-plaintext collision attack method instead of a chosen-plaintext attack. The experimental results show that our proposed approach is better than the existing collision-correlation attack proposed by Clavier et al. at CHES 2011 [11]. To achieve a high key recovery success rate at 80%, we use at least 60% less traces than collision-correlation attack.
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Acknowledgement
This work is supported by Beijing Natural Science Foundation (No. 4202070), National Natural Science Foundation of China (Nos. 61872040, U1836101, 61871037), National Cryptography Development Fund (No. MMJJ20170201), Henan Key Laboratory of Network Cryptography Technology (No. LNCT2019-A02).
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Yang, X., Niu, Y., Tang, Q., Zhang, J., Ding, Y., Wang, A. (2021). Near and Far Collision Attack on Masked AES. In: Liu, Q., Liu, X., Shen, T., Qiu, X. (eds) The 10th International Conference on Computer Engineering and Networks. CENet 2020. Advances in Intelligent Systems and Computing, vol 1274. Springer, Singapore. https://doi.org/10.1007/978-981-15-8462-6_93
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DOI: https://doi.org/10.1007/978-981-15-8462-6_93
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