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Free Fault Leakages for Deep Exploitation: Algebraic Persistent Fault Analysis on Lightweight Block Ciphers
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Abstract: | Persistent Fault Analysis (PFA) is a new fault analysis method for block ciphers proposed in CHES 2018, which utilizes those faults that persist in encryptions. However, one fact that has not been raised enough attention is that: while the fault itself does persist in the entire encryption, the corresponding statistical analysis merely leverages fault leakages in the last one or two rounds, which ignores the valuable leakages in deeper rounds. In this paper, we propose Algebraic Persistent Fault Analysis (APFA), which introduces algebraic analysis to facilitate PFA. APFA tries to make full usage of the free fault leakages in the deeper rounds without incurring additional fault injections. The core idea of APFA is to build similar algebraic constraints for the output of substitution layers and apply the constraints to as many rounds as possible. APFA has many advantages compared to PFA. First, APFA can bypass the manual deductions of round key dependencies along the fault propagation path and transfer the burdens to the computing power of machine solvers such as Crypto-MiniSAT. Second, thanks to the free leakages in the deeper round, APFA requires a much less number of ciphertexts than previous PFA methods, especially for those lightweight block ciphers such as PRESENT, LED, SKINNY, etc. Only 10 faulty ciphertexts are required to recover the master key of SKINNY-64-64, which is about 155 times of reduction as compared to the state-of-the-art result. Third, APFA can be applied to the block ciphers that cannot be analyzed by PFA due to the key size, such as PRESENT-128. Most importantly, APFA replaces statistical analysis with algebraic analysis, which opens a new direction for persistent-fault related researches. |
BibTeX
@article{tches-2022-32058, title={Free Fault Leakages for Deep Exploitation: Algebraic Persistent Fault Analysis on Lightweight Block Ciphers}, journal={IACR Transactions on Cryptographic Hardware and Embedded Systems}, publisher={Ruhr-Universität Bochum}, volume={2022, Issue 2}, pages={289-311}, url={https://tches.iacr.org/index.php/TCHES/article/view/9489}, doi={10.46586/tches.v2022.i2.289-311}, author={Fan Zhang and Tianxiang Feng and Zhiqi Li and Kui Ren and Xinjie Zhao}, year=2022 }