Solving Degree Bounds For Iterated Polynomial Systems
Matthias Johann Steiner

TL;DR
This paper extends the theoretical framework for bounding the solving degree of iterated polynomial systems, providing the first mathematical proofs for complexity bounds of Gr"obner basis attacks on cryptographic ciphers.
Contribution
It generalizes existing bounds to iterated systems used in cryptography, offering new proofs for attack complexities and establishing lower bounds on regularity for certain cipher systems.
Findings
Bounding solving degree for various cipher attacks
First mathematical proofs for attack complexities
Lower bounds on Castelnuovo-Mumford regularity
Abstract
For Arithmetization-Oriented ciphers and hash functions Gr\"obner basis attacks are generally considered as the most competitive attack vector. Unfortunately, the complexity of Gr\"obner basis algorithms is only understood for special cases, and it is needless to say that these cases do not apply to most cryptographic polynomial systems. Therefore, cryptographers have to resort to experiments, extrapolations and hypotheses to assess the security of their designs. One established measure to quantify the complexity of linear algebra-based Gr\"obner basis algorithms is the so-called solving degree. Caminata \& Gorla revealed that under a certain genericity condition on a polynomial system the solving degree is always upper bounded by the Castelnuovo-Mumford regularity and henceforth by the Macaulay bound, which only takes the degrees and number of variables of the input polynomials into…
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Taxonomy
TopicsCoding theory and cryptography · Cryptographic Implementations and Security · Polynomial and algebraic computation
