Abstract
In this article we focus on constructing an algorithm that automatizes the generation of LPN solving algorithms from the considered parameters. When searching for an algorithm to solve an LPN instance, we make use of the existing techniques and optimize their use. We formalize an LPN algorithm as a path in a graph G and our algorithm is searching for the optimal paths in this graph. Our results bring improvements over the existing work, i.e. we improve the results of the covering code from ASIACRYPT’14 and EUROCRYPT’16. Furthermore, we propose concrete practical codes and a method to find good codes.
Cite
CITATION STYLE
Bogos, S., & Vaudenay, S. (2016). Optimization of LPN solving algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10031 LNCS, pp. 703–728). Springer Verlag. https://doi.org/10.1007/978-3-662-53887-6_26
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