Agrawal S., Gentry C., Halevi S., Sahai A.: Discrete Gaussian Leftover Hash Lemma over infinite domains. Cryptology ePrint Archive, Report 2012/714, http://eprint.iacr.org/ (2012). Accessed 27 Dec 2012.
Ajtai M., Kumar R., Sivakumar, D.: Sampling short lattice vectors and the closest lattice vector problem. In: IEEE Conference on Computational Complexity, pp. 53–57 (2002).
Albrecht M.R.: https://bitbucket.org/malb/research-snippets/ (2012). Accessed 30 June 2013.
Albrecht M.R., Farshim P., Faugère J-.C., Perret L.: Polly Cracker, revisited. In: Advances in Cryptology—ASIACRYPT 2011. Lecture Notes in Computer Science, vol. 7073, pp. 179–196. Springer, Berlin. Cryptology ePrint Archive, Report 2011/289, http://eprint.iacr.org/ (2011). Accessed 19 Nov 2012.
Albrecht M., Cid C., Faugère J-.C., Fitzpatrick R., Perret L.: On the complexity of the Arora–Ge algorithm against LWE. In: Faugère J-.C., Gomez D., Gutierrez J., Perret L. (eds.) SCC ’12: Proceedings of the 3nd International Conference on Symbolic Computation and Cryptography, pp. 93–99. Castro-Urdiales, July (2012).
Albrecht M.R., Fitzpatrick R., Cabracas D., Göpfert F., Schneider M.: A generator for LWE and Ring-LWE instances. http://www.iacr.org/news/files/2013-04-29lwe-generator.pdf (2013). Accessed 29 Apr 2013.
Arora S.. Ge R.: New algorithms for learning in presence of errors. In: Aceto L., Henzinger M., Sgall J. (eds.) ICALP. Lecture Notes in Computer Science, vol. 6755, pp. 403–415. Springer, Berlin (2011).
Baigneres T., Junod P., Vaudenay S.: How far can we go beyond linear cryptanalysis? In: Lee P.J. (ed.) Advances in Cryptology—ASIACRYPT 2004. Lecture Notes in Computer Science, vol. 3329, pp. 432–450, Springer, Berlin (2004).
Blum A., Kalai A., Wasserman H.: Noise-tolerant learning, the parity problem, and the statistical query model. J. ACM. 50(4), 506–519 (2003).
Google Scholar
Brakerski Z., Vaikuntanathan V.: Efficient fully homomorphic encryption from (standard) LWE. In: Ostrovsky R. (ed.) IEEE 52nd Annual Symposium on Foundations of Computer Science, FOCS 2011, pp. 97–106. IEEE (2011).
Brakerski Z., Langlois A., Peikert C., Regev O., Stehlé D.: Classical hardness of learning with errors. STOC. (2013) (to appear).
Chen Y., Nguyen P.Q.: BKZ 2.0: better lattice security estimates. In: Lee D.H., Wang X. (eds.) Advances in Cryptology—ASIACRYPT 2011. Lecture Notes in Computer Science, vol. 7073, pp. 1–20, Springer, Berlin (2011).
Duembgen L.: Bounding standard gaussian tail probabilities. arXiv:1012.2063 (2010).
Fouque P-.A., Levieil É.: An improved LPN algorithm. In: De Prisco R., Yung M. (eds.) Security and Cryptography for Networks, 5th International Conference, SCN 2006. Lecture Notes in Computer Science, vol. 4116, pp. 348–359. Springer, Berlin (2006).
Gama N., Nguyen P.Q., Regev O.: Lattice enumeration using extreme pruning. In: Gilbert H. (ed.) Advances in Cryptology—EUROCRYPT 2010. Lecture Notes in Computer Science, vol. 6110, pp. 257–278. Springer, Berlin (2010).
Gentry C.: A fully homomorphic encryption scheme. Ph.D. thesis, Stanford University. http://crypto.stanford.edu/craig (2009).
Gentry C., Peikert C., Vaikuntanathan V.: Trapdoors for hard lattices and new cryptographic constructions. In: STOC 08: Proceedings of the 40th Annual ACM Symposium on Theory of Computing, pp. 197–206. ACM (2008).
Hanrot G., Pujol X., Stehlé, D.: Algorithms for the shortest and closest lattice vector problems. In: Chee Y.M., Guo Z., Ling S., Shao F., Tang Y., Wang H., Xing C. (eds.) IWCC. Lecture Notes in Computer Science, vol. 6639, pp. 159–190. Springer, Berlin (2011).
Hanrot G., Pujol X., Stehlé D.: Analyzing blockwise lattice algorithms using dynamical systems. In: Rogaway P. (ed.) Advances in Cryptology—CRYPTO 2011. Lecture Notes in Computer Science, vol. 6841, pp. 447–464. Springer, Berlin (2011).
Johansson F. et al.: mpmath: a Python library for arbitrary-precision floating-point arithmetic (version 0.17), February 2011. http://code.google.com/p/mpmath/. Accessed 30 June 2013.
Lindner R., Peikert C.: Better key sizes (and attacks) for LWE-based encryption. In: Topics in Cryptology—CT-RSA 2011. Lecture Notes in Computer Science, vol. 6558, pp. 319–339, Springer, Berlin (2011).
Liu M., Nguyen P.Q.: Solving BDD by enumeration: An update. In: Dawson E. (ed.) CT-RSA. Lecture Notes in Computer Science, vol. 7779, pp. 293–309. Springer, Berlin (2013).
Lyubashevsky V., Micciancio D., Peikert C., Rosen A.: SWIFFT: A modest proposal for FFT hashing. In: Nyberg K. (ed.) Fast Software Encryption. Lecture Notes in Computer Science, vol. 5086, pp. 54–72. Springer, Berlin (2008).
Micciancio D., Regev O.: Lattice-based cryptography. In: Bernstein D.J., Buchmann J., Dahmen E. (eds.) Post-Quantum Cryptography, pp. 147–191. Springer, Berlin (2009).
Morel I., Stehlé D., Villard G.: H-LLL: using householder inside LLL. In: Johnson J.R., Park H., Kaltofen E. (eds) Symbolic and Algebraic Computation, International Symposium, ISSAC, 2009 pp. 271–278. ACM (2009).
Nguyen P.Q.: Lattice reduction algorithms: theory and practice. In: Paterson K.G. (eds.) Advances in Cryptology—EUROCRYPT 2011. Lecture Notes in Computer Science, vol. 6632, pp. 2–6. Springer, Berlin (2011).
Nguyen P.Q., Stehlé D.: Low-dimensional lattice basis reduction revisited. ACM Trans. Algorithms 5(4) (2009).
Pujol X., Stehlé D.: Solving the shortest lattice vector problem in time \(2^{2.465n}\). IACR Cryptology ePrint Archive 2009:605 (2009).
Regev O.: On lattices, learning with errors, random linear codes, and cryptography. J. ACM. 56(6), 84–93 (2009).
Google Scholar
Regev O.: The learning with errors problem (invited survey). In: IEEE Conference on Computational Complexity, pp. 191–204. IEEE Computer Society (2010).
Rückert M., Schneider M.: Estimating the security of lattice-based cryptosystems. IACR Cryptology ePrint Archive 2010, 137 (2010).
Stein W.A. et al.: Sage Mathematics Software (Version 5.2). The Sage Development Team, http://www.sagemath.org (2012). Accessed 30 June 2013.