On Worst-Case to Average-Case Reductions for NP Problems

  • Authors:
  • Andrej Bogdanov;Luca Trevisan

  • Affiliations:
  • -;-

  • Venue:
  • FOCS '03 Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science
  • Year:
  • 2003

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Abstract

We show that if an NP-complete problem has a non-adaptive self-corrector with respect to a samplable distribution then coNP is contained in AM/poly and the polynomial hierarchy collapses to the third level. Feigenbaum and Fortnow show the same conclusion under the stronger assumption that an NP-complete problem has a non-adaptive random self-reduction.Our result shows it is impossible (using non-adaptive reductions) to base the average-case hardness of a problem in NP or the security of a one-way function on the worst-case complexity of an NP-complete problem (unless the polynomial hierarchy collapses).