IACR News item: 28 November 2015
Katsuyuki Takashima, Atsushi Takayasu
ePrint Reporte.g. smaller deviations for discrete Gaussian distributions. However, since previous analyses used a fixed order R\\\'enyi divergence, i.e., order two, they lost tightness of reductions. To overcome the deficiency, we adaptively optimize the orders based on the advantages of the adversary for several lattice-based schemes. The optimizations enable us to prove the security with both improved efficiency and tighter reductions. Indeed, our analysis offers security reductions with smaller parameters than the statistical distance based analysis and the reductions are tighter than those of previous R\\\'enyi divergence based analyses. As applications, we show tighter security reductions for sampling discrete Gaussian distributions with smaller precomputed tables for Bimodal Lattice Signature Scheme (BLISS), and the variants of learning with errors (LWE) problem and the small integer solution (SIS) problem called k-LWE and k-SIS, respectively.
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