IACR News item: 18 February 2016
Yoshinori Aono, Yuntao Wang, Takuya Hayashi, Tsuyoshi Takagi
ePrint Report
In this paper, we investigate a variant of the BKZ algorithm,
called progressive BKZ, which performs BKZ reductions
by starting with a small blocksize and gradually switching to larger
blocks as the process continues. We discuss techniques to accelerate the speed of the
progressive BKZ algorithm by optimizing the following parameters:
blocksize, searching radius and probability for pruning of the local enumeration algorithm,
and the constant in the geometric series assumption (GSA).
We then propose a simulator for predicting the length
of the Gram-Schmidt basis obtained from the BKZ reduction.
We also present a model for estimating the
computational cost of the proposed progressive BKZ by
considering the efficient implementation of the local
enumeration algorithm and the LLL algorithm.
Finally, we compare the cost of the proposed progressive
BKZ with that of other algorithms using instances from the Darmstadt SVP Challenge.
The proposed algorithm is approximately 50 times faster than BKZ 2.0 (proposed by Chen-Nguyen) for
solving the SVP Challenge up to 160 dimensions.
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