International Association for Cryptologic Research

International Association
for Cryptologic Research

CryptoDB

Tadanori Teruya

Affiliation: National Institute of Advanced Industrial Science and Technology

Publications

Year
Venue
Title
2018
PKC
Fast Lattice Basis Reduction Suitable for Massive Parallelization and Its Application to the Shortest Vector Problem
The hardness of the shortest vector problem for lattices is a fundamental assumption underpinning the security of many lattice-based cryptosystems, and therefore, it is important to evaluate its difficulty. Here, recent advances in studying the hardness of problems in large-scale lattice computing have pointed to need to study the design and methodology for exploiting the performance of massive parallel computing environments. In this paper, we propose a lattice basis reduction algorithm suitable for massive parallelization. Our parallelization strategy is an extension of the Fukase–Kashiwabara algorithm (J. Information Processing, Vol. 23, No. 1, 2015). In our algorithm, given a lattice basis as input, variants of the lattice basis are generated, and then each process reduces its lattice basis; at this time, the processes cooperate and share auxiliary information with each other to accelerate lattice basis reduction. In addition, we propose a new strategy based on our evaluation function of a lattice basis in order to decrease the sum of squared lengths of orthogonal basis vectors. We applied our algorithm to problem instances from the SVP Challenge. We solved a 150-dimension problem instance in about 394 days by using large clusters, and we also solved problem instances of dimensions 134, 138, 140, 142, 144, 146, and 148. Since the previous world record is the problem of dimension 132, these results demonstrate the effectiveness of our proposal.
2014
EPRINT
2010
EPRINT
High-Speed Software Implementation of the Optimal Ate Pairing over Barreto-Naehrig Curves
This paper describes the design of a fast software library for the computation of the optimal ate pairing on a Barreto--Naehrig elliptic curve. Our library is able to compute the optimal ate pairing over a $254$-bit prime field $\mathbb{F}_{p}$, in just $2.63$ million of clock cycles on a single core of an Intel Core i7 $2.8$GHz processor, which implies that the pairing computation takes $0.942$msec. We are able to achieve this performance by a careful implementation of the base field arithmetic through the usage of the customary Montgomery multiplier for prime fields. The prime field is constructed via the Barreto--Naehrig polynomial parametrization of the prime $p$ given as, $p = 36t^4 +36t^3 +24t^2 +6t+1$, with $t = 2^{62} - 2^{54} + 2^{44}$. This selection of $t$ allows us to obtain important savings for both the Miller loop as well as the final exponentiation steps of the optimal ate pairing.