Abstract
We present a study of the concrete complexity of solving instances of the unique shortest vector problem (uSVP). In particular, we study the complexity of solving the Learning with Errors (LWE) problem by reducing the Bounded-Distance Decoding (BDD) problem to uSVP and attempting to solve such instances using the ‘embedding’ approach. We experimentally derive a model for the success of the approach, compare to alternative methods and demonstrate that for the LWE instances considered in this work, reducing to uSVP and solving via embedding compares favorably to other approaches.
Cite
CITATION STYLE
Albrecht, M. R., Fitzpatrick, R., & Göpfert, F. (2014). On the efficacy of solving LWE by reduction to unique-SVP. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8565, pp. 293–310). Springer Verlag. https://doi.org/10.1007/978-3-319-12160-4_18
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