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On worst-case to average-case reductions for NP problems
Bogdanov, A.   Trevisan, L.  
Comput. Sci. Div., California Univ., Berkeley, CA, USA;

This paper appears in: Foundations of Computer Science, 2003. Proceedings. 44th Annual IEEE Symposium on
Publication Date: 11-14 Oct. 2003
On page(s): 308- 317
ISSN: 0272-5428
ISBN: 0-7695-2040-5
INSPEC Accession Number: 7847057
Current Version Published: 2003-10-20

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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