Paper 2025/586

Heuristic Algorithm for Solving Restricted SVP and its Applications

Abstract

In lattice-based cryptography, many attacks are performed by finding a short enough vector on a specific lattice. However, it is possible that length is not the only restriction on the vector to be found. A typical example is SVP with infinity norm: since most SVP solving algorithms only aim to find short vector under Euclidean norm, the infinity norm is in fact another restriction on the vector. In the literature, such problems are usually solved by performing exhaustive search on a list of short vectors generated from lattice sieving. However, the sieving list might either be too large or too small to pass the additional restriction, which makes the solving algorithm inefficient in some cases. Our contribution in this work is as follows: (1) We formally define a new lattice hard problem called restricted SVP, and show that it can be used to generalize many lattice hard problems, including SVP with non-Euclidean norm and Kannan's embedding on approximate CVP. (2) We extend the dimension for free technique and the enumerate-then-slice technique into approximate SVP where the goal is to output a list of short vectors with a certain size. (3) We give the heuristic algorithm for solving restricted SVP, and design a hardness estimator for this algorithm, which can be used to estimate the concrete hardness of signature forgery in Dilithium and other lattice-based signatures. Using this estimator, we present a concrete security analysis for Dilithium against signature forgery under the gate-count model for the first time. Our estimation matches well with the security estimation from core-SVP model in the document of Dilithium, and we also combine our estimator with the rescaling technique to generate a tighter estimation.