*16:17*[Pub][ePrint] A Full Characterization of Completeness for Two-party Randomized Function Evaluation, by Daniel Kraschewski and Hemanta K. Maji and Manoj Prabhakaran and Amit Sahai

We settle a long standing open problem which has pursued a full characterization of completeness of (potentially randomized) finite functions for 2-party computation that is secure against active adversaries. Since the first such complete function was discovered [Kilian, FOCS 1988], the question of which finite 2-party functions are complete has been studied extensively, leading to characterization in many special cases. In this work, we completely settle this problem.

We provide a polynomial time algorithm to test whether a 2-party finite secure function evaluation (SFE) functionality (possibly randomized) is complete or not. The main tools in our solution include:

-- A formal linear algebraic notion of {\\em redundancy} in a general 2-party randomized function.

-- A notion of {\\em statistically testable games}. A kind of interactive proof in the information-theoretic setting where {\\em both} parties are computationally unbounded but differ in their knowledge of a secret.

-- An extension of the (weak) {\\em converse of Shannon\'s channel coding theorem}, where an adversary can adaptively choose the channel based on it view.

We show that any function $f$, if complete, can implement any (randomized) circuit $C$ using only $O(|C| + k)$ calls to $f$, where $k$ is the statistical security parameter. In particular, for any two-party functionality $g$, this establishes a universal notion of its quantitative ``cryptographic complexity\'\' independent of the setup and has close connections to circuit complexity.