Skip to main content
Log in

A polynomial time algorithm for GapCVPP in l 1 norm

  • Research Paper
  • Published:
Science China Information Sciences Aims and scope Submit manuscript

Abstract

This paper concerns the hardness of approximating the closest vector in a lattice with preprocessing in l 1 norm, and gives a polynomial time algorithm for GapCVPPγ in l 1 norm with gap γ = O(n/logn). The gap is smaller than that obtained by simply generalizing the approach given by Aharonov and Regev. The main technical ingredient used in this paper is the discrete Laplace distribution on lattices which may be of independent interest.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Gauss C F. Disquisitiones Arithmeticae. Leipzig: Gerh Fleischer Iun, 1801

    Google Scholar 

  2. Lenstra A K, Lenstra H W, Lovász L. Factoring polynomials with rational coefficients. Math Ann, 1982, 261: 513–534

    Article  Google Scholar 

  3. Kannan R. Improved algorithms for integer programming and related lattice problems. In: Proceedings of the 15th Annual ACM Symposium on Theory of Computing. New York: ACM, 1983. 193–206

    Google Scholar 

  4. Shamir A. A polynomial time algorithm for breading the basic Merkel-Hellman cryptosystem. In: Proceedings of the 23rd Annual Symposium on Foundations of Computer Science. Washington DC: IEEE, 1982. 145–152

    Google Scholar 

  5. Odlyzko A M. The rise and fall of knapsack cryptosystems. In: Pomerance C, ed. Cryptology and Computational Number Theory. Proceedings of Symposia in Applied Mathematics. Boulder: AMS, 1989. 42: 75–88

    Article  MathSciNet  Google Scholar 

  6. Ajtai M. Generating hard instances of lattice problems (extended abstract). In: Proceedings of the 28th Annual ACM Symposium on Theory of Computing. New York: ACM, 1996. 99–108

    Google Scholar 

  7. Micciancio D. The hardness of the closest vector problem with preprocessing. IEEE Trans Inf Theory, 2001, 47: 1212–1215

    Article  MATH  MathSciNet  Google Scholar 

  8. Regev O. Improved inapproximability of lattice and coding problems with preprocessing. IEEE Trans Inf Theory, 2004, 50: 2031–2037

    Article  MathSciNet  Google Scholar 

  9. Feige U, Micciancio D. The inapproximability of lattice and coding problems with preprocessing. J Comput Syst Sci, 2004, 69: 45–67

    Article  MATH  MathSciNet  Google Scholar 

  10. Van Emde Boas P. Another NP-complete problem and the complexity of computing short vectors in a lattice. Technical Report 81–04, Math Inst, University of Amsterdam, Amsterdam, 1981

    Google Scholar 

  11. Dinur I. Approximating SVP to within almost-polynomial factors is NP-hard. Theor Comput Sci, 2002, 285: 55–71

    Article  MATH  MathSciNet  Google Scholar 

  12. Dinur I, Kindler G, Raz R, et al. Approximating CVP to within almost polynomial factors is NP-hard. Combinatorica, 2003, 23: 205–243

    Article  MATH  MathSciNet  Google Scholar 

  13. Alekhnovich M, Khot S, Kindler G, et al. Hardness of approximating the closest vector problem with preprocessing. In: Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science. Washington DC: IEEE, 2005. 216–225

    Google Scholar 

  14. Regev O, Rosen R. Lattice problems and norm embeddings. In: Proceedings of the 38th Annual ACM Symposium on Theory of Computing. New York: ACM, 2006. 447–456

    Google Scholar 

  15. Aharonov D, Regev O. Lattice problems in NP coNP. J ACM, 2005, 52: 749–765

    Article  MATH  MathSciNet  Google Scholar 

  16. Banaszczyk W. Inequalites for convex bodies and polar reciprocal lattices in ℝn. Discret Comput Geom, 1995, 13: 217–231

    Article  MATH  MathSciNet  Google Scholar 

  17. Peikert C. Limits on the hardness of lattice problems in l p norms. Comput Complex, 2008, 17: 300–351

    Article  MATH  MathSciNet  Google Scholar 

  18. Ebeling W. Lattices and Codes. Advanced Lectures in Mathematics. Revised edition. Braunschweig: Friedr Vieweg & Sohn, 2002

    Book  Google Scholar 

  19. Micciancio D, Regev O. Worst-case to average-case reductions based on Gaussian measures. SIAM J Comput, 2007, 37: 267–302

    Article  MATH  MathSciNet  Google Scholar 

  20. Hoeffding W. Probability inequalities for sums of bounded random variables. J Am Stat Assoc, 1963, 58: 13–30

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to ChengLiang Tian.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Tian, C., Han, L. & Xu, G. A polynomial time algorithm for GapCVPP in l 1 norm. Sci. China Inf. Sci. 57, 1–7 (2014). https://doi.org/10.1007/s11432-013-4795-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11432-013-4795-8

Keywords

Navigation