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Random Probing Security with Precomputation
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| Abstract: | At Eurocrypt 2014, Duc, Dziembowski and Faust proposed the random probing model to bridge the gap between the probing model proposed at Crypto 2003 and the noisy model proposed at Eurocrypt 2013. Compared with the probing model whose noise in the leakages should (linearly) increase with the number of shares, the random probing model allows each variable leak its value with a probability p, which reflects the physical reality of side channels much better. In Crypto 2020, Belaïd et al. proposed the Random Probing Expandability (RPE) security ensuring the random probing security for arbitrary order masking algorithms with constant leakage probability. However, the complexity of existing RPE algorithms is much higher than that of the probing secure algorithms, which is short of practical usage. In this paper, we investigate the random probing security with precomputation, where a masked cryptographic implementation can be divided into two phases. The first phase, called preprocessing, takes random bits and returns a number of precomputed values. The second phase, called online computation, takes input (e.g., plaintext and shares of secret) and precomputed values to calculate output (e.g., ciphertext) efficiently. We describe a random probing secure precomputable scheme, which transforms an arbitrary circuit compiler with tolerant leakage probability p into a precomputable one by adding a public (but random) share that is calculated in the online phase and the tolerant leakage probability of the new compiler is min{p, 2−5.01}. Then, we apply the new scheme to the bitsliced AES. Notably, the implementation under ARM Cortex M architecture shows that the performance of the online phase is significantly improved and even comparable to masking schemes only secure in the probing model. |
BibTeX
@article{tches-2024-34885,
title={Random Probing Security with Precomputation},
journal={IACR Transactions on Cryptographic Hardware and Embedded Systems},
publisher={Ruhr-Universität Bochum},
volume={2025},
pages={523-551},
url={https://tches.iacr.org/index.php/TCHES/article/view/11943},
doi={10.46586/tches.v2025.i1.523-551},
author={Bohan Wang and Fanjie Ji and Yiteng Sun and Weijia Wang},
year=2024
}