Sieve algorithms for the discrete logarithm in medium characteristic finite fields

Laurent Grémy 1
1 CARAMBA - Cryptology, arithmetic : algebraic methods for better algorithms
LORIA - ALGO - Department of Algorithms, Computation, Image and Geometry, Inria Nancy - Grand Est
Abstract : The security of public-key cryptography relies mainly on the difficulty to solve some mathematical problems, among which the discrete logarithm problem on finite fields GF(p^n). In this thesis, we study the variants of the number field sieve (NFS) algorithm, which solve the most efficiently this problem, in the case where the characteristic of the field is medium. The NFS algorithm can be divided into four main steps: the polynomial selection, the relation collection, the linear algebra and the computation of an individual logarithm. We describe these steps and focus on the relation collection, one of the most costly steps. A way to perform it efficiently is to make use of sieve algorithms. Contrary to the classical case for which the relation collection takes place in a two-dimensional space, the finite fields we target require the enumeration of elements in a higher-dimensional space to reach the best theoretical complexity. There exist efficient sieve algorithms in two dimensions, but only a few in higher dimensions. We propose and study two new sieve algorithms allowing us to treat any dimensions, with an emphasis on the three-dimensional case. We have provided a complete implementation of the relation collection for some variants of the NFS in three dimensions. This implementation relies on our new sieve algorithms and is distributed in the CADO-NFS software. We validated its performances by comparing with examples from the literature. We also establish two new discrete logarithm record computations, one in a 324-bit GF(p^5) and one in a 422-bit GF(p^6)
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Laurent Grémy. Sieve algorithms for the discrete logarithm in medium characteristic finite fields. Cryptography and Security [cs.CR]. Université de Lorraine, 2017. English. ⟨NNT : 2017LORR0141⟩. ⟨tel-01647623⟩

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