Secure Computation From Millionaire

The standard method for designing a secure computation protocol for function f first transforms f into either a circuit or a RAM program and then applies a generic secure computation protocol that either handles boolean gates or translates the RAM program into oblivious RAM instructions. In this paper, we show a large class of functions for which a different iterative approach to secure computation results in more efficient protocols. The first such examples of this technique was presented by Aggarwal, Mishra, and Pinkas (J. of Cryptology, 2010) for computing the median; later, Brickell and Shmatikov (Asiacrypt 2005) showed a similar technique for shortest path problems. We generalize the technique in both of those works and show that it applies to a large class of problems including certain matroid optimizations, sub-modular optimization, convex hulls, and other scheduling problems. The crux of our technique is to securely reduce these problems to secure comparison operations and to employ the idea of gradually releasing part of the output. We then identify conditions under which both of these techniques for protocol design are compatible with achieving simulationbased security in the honest-but-curious and covert adversary models. In special cases such as median, we also show how to achieve malicious security.