A hierarchy of polynomial time lattice basis reduction algorithms
Theoretical Computer Science
Lattice basis reduction: improved practical algorithms and solving subset sum problems
Mathematical Programming: Series A and B
A sieve algorithm for the shortest lattice vector problem
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Sampling methods for shortest vectors, closest vectors and successive minima
Theoretical Computer Science
Improved analysis of Kannan's shortest lattice vector algorithm
CRYPTO'07 Proceedings of the 27th annual international cryptology conference on Advances in cryptology
EUROCRYPT'08 Proceedings of the theory and applications of cryptographic techniques 27th annual international conference on Advances in cryptology
Proceedings of the forty-second ACM symposium on Theory of computing
Faster exponential time algorithms for the shortest vector problem
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Accelerating lattice reduction with FPGAs
LATINCRYPT'10 Proceedings of the First international conference on Progress in cryptology: cryptology and information security in Latin America
ANTS'06 Proceedings of the 7th international conference on Algorithmic Number Theory
Lattice enumeration using extreme pruning
EUROCRYPT'10 Proceedings of the 29th Annual international conference on Theory and Applications of Cryptographic Techniques
Parallel shortest lattice vector enumeration on graphics cards
AFRICACRYPT'10 Proceedings of the Third international conference on Cryptology in Africa
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Lattice based cryptography is gaining more and more importance in the cryptographic community. The security of lattice based cryptosystems can be proven to be as hard as worst case lattice problems. The most important underlying hard problem is the shortest vector problem. There are two concurrent approaches for the search for shortest vectors in lattices: enumeration and probabilistic sieving algorithms. Enumeration algorithms were the best choice, until in 2010, Micciancio and Voulgaris present a new heuristic sieving algorithm called Gauss Sieve, which was the first sieving algorithm considered to be competitive to exhaustive search algorithms. Later in 2010, Gama, Nguyen, and Regev published their extreme pruning variant of the enumeration, which again ruled out sieving. In this paper, we present the practical results using Gauss Sieve that we gained in our experiments throughout the last year. We analyze the behaviour of Gauss Sieve that helps understanding the strengths and weaknesses of the algorithm.