Root optimization of polynomials in the number field sieve

The general number field sieve (GNFS) is the most efficient algorithm known for factoring large integers. It consists of several stages, the first one being polynomial selection. The quality of the chosen polynomials in polynomial selection can be modelled in terms of size and root properties. In this paper, we describe some algorithms for selecting polynomials with very good root properties.Comment: 16 pages, 18 reference

An Implementation of the Extended Tower Number Field Sieve using 4d Sieving in a Box and a Record Computation in Fp4

We report on an implementation of the Extended Tower Number Field Sieve (ExTNFS) and record computation in a medium characteristic finite field Fp4 of 512 bits size. We show that sieving in a box (orthotope) for collecting relations for ExTNFS is still fast in 4 dimensions

Root optimization of polynomials in the number field sieve

International audienceThe general number field sieve (GNFS) is the most efficient algorithm known for factoring large integers. It consists of several stages, the first one being polynomial selection. The quality of the chosen polynomials in polynomial selection can be modelled in terms of size and root properties. In this paper, we describe some algorithms for selecting polynomials with very good root properties

Solving a 676-Bit Discrete Logarithm Problem in GF(36n )

Pairings on elliptic curves over finite fields are crucial for constructing various cryptographic schemes. The \eta_T pairing on supersingular curves over GF(3^n) is particularly popular since it is efficiently implementable. Taking into account the Menezes-Okamoto-Vanstone (MOV) attack, the discrete logarithm problem (DLP) in GF(3^{6n}) becomes a concern for the security of cryptosystems using \eta_T pairings in this case. In 2006, Joux and Lercier proposed a new variant of the function field sieve in the medium prime case, named JL06-FFS. We have, however, not yet found any practical implementations on JL06-FFS over GF(3^{6n}). Therefore, we first fulfilled such an implementation and we successfully set a new record for solving the DLP in GF(3^{6n}), the DLP in GF(3^{6 \cdot 71}) of 676-bit size. In addition, we also compared JL06-FFS and an earlier version, named JL02-FFS, with practical experiments. Our results confirm that the former is several times faster than the latter under certain conditions

Relation collection for the Function Field Sieve

International audienceIn this paper, we focus on the relation collection step of the Function Field Sieve (FFS), which is to date the best known algorithm for computing discrete logarithms in small-characteristic finite fields of cryptographic sizes. Denoting such a finite field by GF(p^n), where p is much smaller than n, the main idea behind this step is to find polynomials of the form a(t)-b(t)x in GF(p)[t][x] which, when considered as principal ideals in carefully selected function fields, can be factored into products of low-degree prime ideals. Such polynomials are called ''relations'', and current record-sized discrete-logarithm computations require billions of them. Collecting relations is therefore a crucial and extremely expensive step in FFS, and a practical implementation thereof requires heavy use of cache-aware sieving algorithms, along with efficient polynomial arithmetic over GF(p)[t]. This paper presents the algorithmic and arithmetic techniques which were put together as part of a new implementation of FFS, aimed at medium- to record-sized computations, and planned for public release in the near future

We Are on the Same Side. Alternative Sieving Strategies for the Number Field Sieve

The Number Field Sieve (NFS) is the state-of-the art algorithm for integer factoring, and sieving is a crucial step in the NFS. It is a very time-consuming operation, whose goal is to collect many relations. The ultimate goal is to generate random smooth integers mod $N$ with their prime decomposition, where smooth is defined on the rational and algebraic sides according to two prime factor bases. In modern factorization tool, such as \textsf{Cado-NFS}, sieving is split into different stages depending on the size of the primes, but defining good parameters for all stages is based on heuristic and practical arguments. At the beginning, candidates are sieved by small primes on both sides, and if they pass the test, they continue to the next stages with bigger primes, up to the final one where we factor the remaining part using the ECM algorithm. On the one hand, first stages are fast but many false relations pass them, and we spend a lot of time with useless relations. On the other hand final stages are more time demanding but outputs less relations. It is not easy to evaluate the performance of the best strategy on the overall sieving step since it depends on the distribution of numbers that results at each stage. In this article, we try to examine different sieving strategies to speed up this step since many improvements have been done on all other steps of the NFS. Based on the relations collected during the RSA-250 factorization and all parameters, we try to study different strategies to better understand this step. Many strategies have been defined since the discovery of NFS, and we provide here an experimental evaluation