Lattice sieving via quantum random walks
This work addresses cryptanalysis for post-quantum cryptography, offering an incremental improvement in quantum algorithms for lattice sieving.
The authors tackled the Shortest Vector Problem (SVP) in lattice-based cryptography by improving the best quantum algorithm's running time from 2^{0.2653d + o(d)} to 2^{0.2570d + o(d)} for lattice dimension d, and presented time-memory trade-offs.
Lattice-based cryptography is one of the leading proposals for post-quantum cryptography. The Shortest Vector Problem (SVP) is arguably the most important problem for the cryptanalysis of lattice-based cryptography, and many lattice-based schemes have security claims based on its hardness. The best quantum algorithm for the SVP is due to Laarhoven [Laa16 PhD] and runs in (heuristic) time $2^{0.2653d + o(d)}$. In this article, we present an improvement over Laarhoven's result and present an algorithm that has a (heuristic) running time of $2^{0.2570 d + o(d)}$ where $d$ is the lattice dimension. We also present time-memory trade-offs where we quantify the amount of quantum memory and quantum random access memory of our algorithm. The core idea is to replace Grover's algorithm used in [Laa16 PhD] in a key part of the sieving algorithm by a quantum random walk in which we add a layer of local sensitive filtering.