This paper takes the next step in developing the theory of average case complexity initiated by Leonid A Levin. Previous works [Levin 84, Gurevich 87, Venkatesan and Levin 88] have focused on the existence of complete problems. We widen the scope to other basic questions in computational complexity. Our results include: ffl the equivalence of search and decision problems in the context of average case complexity; ffl an initial analysis of the structure of distributional-NP (i.e. NP problems coupled with "simple distributions") under reductions which preserve average polynomial-time; ffl a proof that if all of distributional-NP is in average polynomial-time then non-deterministic exponential-time equals deterministic exponential time (i.e., a collapse in the worst case hierarchy); ffl definitions and basic theorems regarding other complexity classes such as average log-space. An exposition of the basic definitions suggested by Levin and suggestions for some alternative definitions ...

) Donald Beaver Harvard University Silvio Micali y MIT Phillip Rogaway y MIT Abstract In a network of n players, each player i having private input x i , we show how the players can collaboratively evaluate a function f(x 1 ; : : : ; xn ) in a way that does not compromise the privacy of the players' inputs, and yet requires only a constant number of rounds of interaction. The underlying model of computation is a complete network of private channels, with broadcast, and a majority of the players must behave honestly. Our solution assumes the existence of a one-way function. 1 Introduction Secure function evaluation. Assume we have n parties, 1; : : : ; n; each party i has a private input x i known only to him. The parties want to correctly evaluate a given function f on their inputs, that is to compute y = f(x 1 ; : : : ; xn ), while maintaining the privacy of their own inputs. That is, they do not want to reveal more than the value y implicitly reveals. Secure function evaluat...