skip to main content
10.1145/3087604.3087665acmotherconferencesArticle/Chapter ViewAbstractPublication PagesissacConference Proceedingsconference-collections
research-article

Lattice Reduction Algorithms

Published:23 July 2017Publication History

ABSTRACT

Lattice reduction aims at finding a basis consisting of rather short vectors, from an arbitrary basis of a Euclidean lattice. The importance of lattice reduction stems from the observation that many computational problems can be cast as finding short non-zero vectors in specific lattices (e.g., in computer algebra, cryptography and algorithmic number theory).

In this tutorial, we give an overview of lattice reduction algorithms. We will consider both polynomial-time algorithms that find relatively short bases, such as the LLL algorithm, and more expensive algorithms that find shorter bases, such as the BKZ algorithm. The algorithms will be illustrated using the fplll library.

References

  1. Divesh Aggarwal, Daniel Dadush, Oded Regev, and Noah Stephens-Davidowitz. 2015. Solving the Shortest Vector Problem in 2n Time Using Discrete Gaussian Sampling. In Proc. of STOC. ACM, pages 733--742. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Erik Agrell, Thomas Eriksson, Alexander Vardy, and Kenneth Zeger. 2002. Closest point search in lattices. IEEE Trans. Inf. Th. 48, 8 (2002), pages 2201--2214. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Miklós Ajtai. 1998. The shortest vector problem in L_2 is NP-hard for randomized reductions. In Proc. of STOC. ACM, pages 284--293. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. M. Ajtai, R. Kumar, and D. Sivakumar. 2001. A sieve algorithm for the shortest lattice vector problem. In Proc. of STOC. ACM, pages 601--610. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Jens Bauch, Daniel J. Bernstein, Henry de Valence, Tanja Lange, and Christine van Vredendaal. 2017. Short Generators Without Quantum Computers: The Case of Multiquadratics. In Proc. of EUROCRYPT (LNCS), Vol. 10210. Springer, pages 27--59.Google ScholarGoogle Scholar
  6. Anja Becker, Léo Ducas, Nicolas Gama, and Thijs Laarhoven. 2016. New directions in nearest neighbor searching with applications to lattice sieving. In Proc. of SODA. SIAM, pages 10--24. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Peter Campbell, Michael Groves, and Dan Shepherd. 2014. Soliloquy: A cautionary tale. In ETSI 2nd Quantum-Safe Crypto Workshop. pages 1--9.Google ScholarGoogle Scholar
  8. Xiao-Wen Chang, Damien Stehlé, and Gilles Villard. 2012. Perturbation Analysis of the QR factor R in the context of LLL lattice basis reduction. Math. Comput. 81, 279 (2012), pages 1487--1511.Google ScholarGoogle Scholar
  9. Yuanmi Chen and Phong Q. Nguyen. 2011. BKZ 2.0: Better Lattice Security Estimates. In Proc. of ASIACRYPT (LNCS), Vol. 7073. Springer, pages 1--20. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Henri Cohen. 1995. A Course in Computational Algebraic Number Theory, 2nd edition. Springer.Google ScholarGoogle Scholar
  11. Ronald Cramer, Léo Ducas, Chris Peikert, and Oded Regev. 2016. Recovering Short Generators of Principal Ideals in Cyclotomic Rings. In Proc. of EUROCRYPT (LNCS), Vol. 9666. Springer, pages 559--585.Google ScholarGoogle Scholar
  12. Ronald Cramer, Léo Ducas, and Benjamin Wesolowski. 2017. Short Stickelberger Class Relations and Application to Ideal-SVP. In Proc. of EUROCRYPT (LNCS), Vol. 10210. Springer, pages 324--348.Google ScholarGoogle Scholar
  13. The FPLLL development team. 2016. fplll, a lattice reduction library. (2016). Available at https://github.com/fplll/fplll.Google ScholarGoogle Scholar
  14. Ulrich Fincke and Michael Pohst. 1983. A procedure for determining algebraic integers of given norm. In Proc. of EUROCAL (LNCS), Vol. 162. Springer, pages 194--202. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Nicolas Gama, Nick Howgrave-Graham, Henrik Koy, and Phong Q. Nguyen. 2006. Rankin's Constant and Blockwise Lattice Reduction. In Proc. of CRYPTO (LNCS), Vol. 4117. Springer, pages 112--130. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Nicolas Gama and Phong Q. Nguyen. 2008. Finding Short Lattice Vectors within Mordell's Inequality. In Proc. of STOC. ACM, pages 207--216. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Nicolas Gama, Phong Q. Nguyen, and Oded Regev. 2010. Lattice Enumeration Using Extreme Pruning. In Proc. of EUROCRYPT (LNCS), Vol. 6110. Springer, pages 257--278. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Guillaume Hanrot, Xavier Pujol, and Damien Stehlé. 2011. Analyzing Blockwise Lattice Algorithms Using Dynamical Systems. In Proc. of CRYPTO (LNCS), Vol. 6841. Springer, pages 447--464. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Hoeijvan Hoeij. 2001. Factoring polynomials and 0--1 vectors. In Proc. of CALC (LNCS), Vol. 2146. Springer, pages 45--50. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Johan Hastad, Bettina Just, Jeffrey C. Lagarias, and Claus-Peter Schnorr. 1989. Polynomial Time Algorithms for Finding Integer Relations Among Real Numbers. SIAM J. Comput 18, 5 (1989), pages 859--881. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Ravi Kannan. 1983. Improved algorithms for integer programming and related lattice problems. In Proc. of STOC. ACM, pages 99--108. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Henrik Koy and Claus-Peter Schnorr. 2001. Segment LLL-reduction of lattice bases. In Proc. of CALC (LNCS), Vol. 2146. Springer, pages 67--80. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Thijs Laarhoven. 2015. Search problems in cryptography. Ph.D. Dissertation. Eindhoven University of Technology. http://www.thijs.com/docs/phd-final.pdf.Google ScholarGoogle Scholar
  24. Arjen K. Lenstra, Hendrik W. Lenstra, Jr., and László Lovász. 1982. Factoring polynomials with rational coefficients. Math. Ann 261 (1982), pages 515--534.Google ScholarGoogle Scholar
  25. Alexander May. 2009. Using LLL-Reduction for Solving RSA and Factorization Problems: A Survey. (2009). Chapter ofciteLLL25.Google ScholarGoogle Scholar
  26. Daniele Micciancio and Panagiotis Voulgaris. 2010. A deterministic single exponential time algorithm for most lattice problems based on Voronoi cell computations. In Proc. of STOC. ACM, pages 351--358. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Ivan Morel, Damien Stehlé, and Gilles Villard. 2009. H-LLL: using Householder inside LLL. In Proc. of ISSAC. ACM, pages 271--278. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Arnold Neumaier and Damien Stehlé. 2016. Faster LLL-type Reduction of Lattice Bases. In Proc. of ISSAC. ACM, pages 373--380. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Phong Q. Nguyen and Damien Stehlé. 2009. An LLL algorithm with quadratic complexity. SIAM J. Comput 39, 3 (2009), pages 874--903. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. P. Q. Nguyen and J. Stern. 2001. The Two Faces of Lattices in Cryptology. In Proc. of CALC (LNCS), Vol. 2146. Springer, pages 146--180. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Phong Q. Nguyen and Brigitte Vallée. 2009. The LLL Algorithm: Survey and Applications. Springer. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Andrew Novocin, Damien Stehlé, and Gilles Villard. 2011. An LLL-reduction algorithm with quasi-linear time complexity. In Proc. of STOC. ACM, pages 403--412. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Andrew M. Odlyzko. 1989. The Rise and Fall of Knapsack Cryptosystems. In Proceedings of Cryptology and Computational Number Theory (Proceedings of Symposia in Applied Mathematics), Vol. 42. American Mathematical Society, pages 75--88.Google ScholarGoogle Scholar
  34. Chris Peikert. 2016. A Decade of Lattice Cryptography. Foundations and Trends in Theoretical Computer Science 10, 4 (2016), pages 283--424. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Xavier Pujol and Damien Stehlé. 2009. Solving the Shortest Lattice Vector Problem in Time 2 2.465n. Cryptology ePrint Archive. (2009). http://eprint.iacr.org/2009/605.Google ScholarGoogle Scholar
  36. Claus-Peter Schnorr. 2011. Accelerated Slide- and LLL-Reduction. Electronic Colloquium on Computational Complexity (ECCC) 18 (2011), pages 50. http://eccc.hpi-web.de/report/2011/050Google ScholarGoogle Scholar
  37. Claus-Peter Schnorr. 1987. A Hierarchy of Polynomial Lattice Basis Reduction Algorithms. Theor. Comput. Science 53 (1987), pages 201--224. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Claus-Peter Schnorr. 1988. A more efficient algorithm for lattice basis reduction. Journal of Algorithms 9, 1 (1988), pages 47--62. Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. Claus-Peter Schnorr and Michael Euchner. 1994. Lattice basis reduction: improved practical algorithms and solving subset sum problems. Mathematics of Programming 66 (1994), pages 181--199. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. Arnold Schönhage. 1984. Factorization of univariate integer polynomials by Diophantine approximation and improved basis reduction algorithm. In Proc. of ICALP (LNCS), Vol. 172. Springer, pages 436--447. Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. Arne Storjohann. 1996. Faster algorithms for integer lattice basis reduction. (1996). Technical report, ETH Zürich.Google ScholarGoogle Scholar

Index Terms

  1. Lattice Reduction Algorithms

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Other conferences
      ISSAC '17: Proceedings of the 2017 ACM on International Symposium on Symbolic and Algebraic Computation
      July 2017
      466 pages
      ISBN:9781450350648
      DOI:10.1145/3087604

      Copyright © 2017 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 23 July 2017

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article

      Acceptance Rates

      Overall Acceptance Rate395of838submissions,47%

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader