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On worst-case to average-case reductions for NP problems

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This paper appears in:
Foundations of Computer Science, 2003. Proceedings. 44th Annual IEEE Symposium on
Date of Conference: 11-14 Oct. 2003
Author(s): Bogdanov, A.
Comput. Sci. Div., California Univ., Berkeley, CA, USA
Trevisan, L.
Page(s): 308 - 317
Product Type: Conference Publications

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Abstract

We show that if an NP-complete problem has a non-adaptive self-corrector with respect to a distribution that can be sampled 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).

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