AI & ML
Provably Subexponential Algorithms for Bounded-Error LWE with Few Samples
arXiv cs.CR0 views
arXiv:2610.13043v1 Announce Type: new Abstract: We show that a variant of the Wagner/BKW-style algorithm for LWE of Kirchner and Fouque [KF15] solves decision and search LWE with secrets of size $n$ over prime moduli $q=n^{\kappa+o(1)}$, for any fixed $\kappa>0$, with errors bounded by $\exp((\ln n)^{o(1)})$, in time $2^{O(n/\ln\ln n)}$ given $n+O(n/\ln\ln n)$ original samples. Further, if each coordinate of the secret is also bounded by $\exp((\ln n)^{o(1)})$, the same time bound holds with errors bounded by $n^{o(1)}$ and only $O(n/\ln\ln q)$ samples. Earlier, it was known that Kirchner and Fouque's algorithm could solve LWE with these parameters in subexponential time with a much larger number of samples $m = \Omega(n\log{n})$ [HKM18]. Ducas et al. [DEL25] showed that an adaptation of this algorithm could solve the corresponding dual, the $\mathrm{SIS}^{\infty}$ problem, with a suitable norm bound $q/\operatorname{polylog}(n)$ and $m=n+\omega(n/\ln\ln n)$ variables in subexponential time. Whereas their analysis involves interpreting the algorithm in terms of chains of lattices, our approach is quite elementary and is based on bounding the lower moments of a Fourier statistic.
Source:https://arxiv.org/abs/2610.13043PreviousPost-Quantum Session Establishment for Matter over Thread: Message Size, Transport, and Protocol OptionsNextSpace Over Statistic, Retraining Over Ranking: Auditing Training Labels Under Label-Only Backdoors
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