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The Shortest Vector Problem (SVP) is one of the mathematical foundations of lattice based cryptography. Lattice sieve algorithms are amongst the foremost methods of solving SVP. The asymptotically fas...
Abstract. There is a large gap between theory and practice in the complexities of sieving algorithms for solving the shortest vector problem in an arbitrary Euclidean lattice. In this paper, we work t...
The Learning with Errors problem (LWE) has become a central topic in recent cryptographic research. In this paper, we present a new solving algorithm combining important ideas from previous work on im...
Since 2016 and the introduction of the exTNFS (extended Tower Number Field Sieve) algorithm, the security of cryptosystems based on non- prime finite fields, mainly the paring and torus-based one, is ...
In this work we consider a progressive approach to lattice sieving, where we gradually introduce new basis vectors only when the sieve has stabilized on the previous basis vectors. This leads to impro...
Our results extend and improve upon previous work of Bai-Laarhoven-Stehlé [ANTS'16] and Herold-Kirshanova [PKC'17], with better complexities for arbitrary tuple sizes and offering tunable time-memory ...
Asymptotically, the best known algorithms for solving the Shortest Vector Problem (SVP) in a lattice of dimension nn are sieve algorithms, which have heuristic complexity estimates ranging from (4/3)n...
In practice, the large memory footprint makes it problematic to run sieving directly on high-dimensional lattices, and perhaps the most promising application of such algorithms is as part of a hybrid ...
Lattice sieving is asymptotically the fastest approach for solving the shortest vector problem (SVP) on Euclidean lattices. All known sieving algorithms for solving SVP require space which (heuristica...
By replacing the brute-force list search in sieving algorithms with Charikar's angular locality-sensitive hashing (LSH) method, we get both theoretical and practical speedups for solving the shortest ...
The security of many lattice-based cryptographic schemes relies on the hardness of finding short vectors in integral lattices. We propose a new variant of the parallel Gauss sieve algorithm to compu...
In this paper, we assess the practicability of HashSieve, a recently proposed sieving algorithm for the Shortest Vector Problem (SVP) on lattices, on multi-core shared memory systems. To this end, we ...
Many cryptographic protocols derive their security from the apparent computational intractability of the integer factorization problem. Currently, the best known integer-factoring algorithms run in ...
Recently, it was shown that angular locality-sensitive hashing (LSH) can be used to significantly speed up lattice sieving, leading to a heuristic time complexity for solving the shortest vector probl...
We give a simple heuristic sieving algorithm for the m-dimensional exact shortest vector problem (SVP) which runs in time 20.3112m+o(m) . Unlike previous time-memory trade-offs, we do not increase ...

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