Abstract
We compare two key recovery methods for single trace attacks on the AES key schedule. The 2018 CHES capture-the-flag (CTF) challenge which includes an unprotected key schedule raises the question, which method performs best during key recovery: Soft Analytical Side-Channel Attacks (SASCAs) or Algebraic Side-Channel Attacks (ASCAs). SASCAs as well as ASCAs exploit knowledge about the attacked algorithm by leakage recombination and allow for a computationally efficient key recovery based on e.g. Hamming Weight (HW) leakage. We use Belief Propagation (BP), which is the most popular choice for SASCA and a SAT solver as an ASCA algorithm. In this work we attack real traces of the CTF challenge to demonstrate the limitations of SASCAs while handling the XOR operation. We exemplify that SASCAs may not always be the most favorable solution. The comparison is solidified by evaluating the success rate of SASCAs and ASCAs with simulated HW leakage on varying noise levels. During attacks on the AES key schedule the convergence of BP is not only graph dependent but data dependent. Further, we discuss possible graph clusters and adaptations of the input distributions to mitigate the influence of the XOR operations and increase the success rate of BP. All experiments are compared against equivalent SAT solver approaches. Based on our results we propose a combination of brute-force and BP to level the performance of the SAT solver and BP. Apart from this, we address unsolved questions regarding the benefit of an early break of BP and point out implementation details which lead to a better success rate.
J. Heyszl and F. Unterstein—Work was done while the author was at Fraunhofer AISEC.
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Acknowledgements
This work was supported by the German Ministry of Education, Research and Technology in the context of the project Aquorypt (reference numbers 16KIS1018).
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Strieder, E., Ilg, M., Heyszl, J., Unterstein, F., Streit, S. (2023). ASCA vs. SASCA. In: Kavun, E.B., Pehl, M. (eds) Constructive Side-Channel Analysis and Secure Design. COSADE 2023. Lecture Notes in Computer Science, vol 13979. Springer, Cham. https://doi.org/10.1007/978-3-031-29497-6_4
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