At SODA 2017 Lokshtanov et al. presented the first worst-case algorithms with exponential speedup over exhaustive search for solving polynomial equation systems of degree $d$ in $n$ variables over finite fields. These algorithms were based on the polynomial method in circuit complexity which is a technique for proving circuit lower bounds that has recently been applied in algorithm design. Subsequent works further improved the asymptotic complexity of polynomial method-based algorithms for solving equations over the field $mathbb{F}_2$. However, the asymptotic complexity formulas of these algorithms hide significant low-order terms, and hence they outperform exhaustive search only for very large values of $n$.

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In this paper, we devise a concretely efficient polynomial method-based algorithm for solving multivariate equation systems over $mathbb{F}_2$. We analyze our algorithm’s performance for solving random equation systems, and bound its complexity by about $n^2 cdot 2^{0.815n}$ bit operations for $d = 2$ and $n^2 cdot 2^{left(1 – 1/2.7dright) n}$ for any $d geq 2$.

We apply our algorithm in cryptanalysis of recently proposed instances of the Picnic signature scheme (an alternate third-round candidate in NIST’s post-quantum standardization project) that are based on the security of the LowMC block cipher. Consequently, we show that 2 out of 3 new instances do not achieve their claimed security level. As a secondary application, we also improve the best-known preimage attacks on several round-reduced variants of the Keccak hash function.

Our algorithm combines various techniques used in previous polynomial method-based algorithms with new optimizations, some of which exploit randomness assumptions about the system of equations. In its cryptanalytic application to Picnic, we demonstrate how to further optimize the algorithm for solving structured equation systems that are constructed from specific cryptosystems.

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