A fundamental problem in the theory of secure multi-party computation (MPC) is to characterize functions with more than 2 parties which admit MPC protocols with information-theoretic security against passive corruption. This question has seen little progress since the work of Chor and Ishai (2001), which demonstrated difficulties in resolving it. In this work, we make significant progress towards resolving this question in the important case of aggregating functionalities, in which m parties P1, . . . , Pm hold inputs x1, . . . , xm and an aggregating party P0 must learn f(x1, . . . , xm). We give a necessary condition and a slightly stronger sufficient condition for f to admit a secure protocol. Both the conditions are stated in terms of an algebraic structure we introduce called Commuting Permutations Systems (CPS), which may be of independent combinatorial interest. When our sufficiency condition is met, we obtain a perfectly secure protocol with minimal interaction, that fits the model of Non-Interactive MPC or NIMPC (Beimel et al., 2014), but without the need for a trusted party to generate correlated randomness. We define Unassisted Non-Interactive MPC (UNIMPC) to capture this variant. We also present an NIMPC protocol for all functionalities, which is simpler and more efficient than the one given in the prior work. 2012 ACM Subject Classification Theory of computation → Cryptographic protocols, Theory of computation → Complexity classes, Security and privacy → Mathematical foundations of

Brief Announcement: On Secure m-Party Computation, Commuting Permutation Systems and Unassisted Non-Interactive MPC.

In an influential work aimed at understanding the communication requirements of secure computation, Feige, Kilian and Naor introduced a minimal model of secure computation (STOC 1994). In that work, among other results, Feige et al. presented a simple protocol for the 2 input AND function. It has remained an intriguing question whether the communication and randomness used in this protocol are optimal. While previous work of Data et al. (CRYPTO 2014) showed that the communication from the two parties with inputs (Alice and Bob) to the third party who gets the output is optimal, the question of optimality for the third message in the protocol – a common reference string shared between Alice and Bob – remained open. In this note we show that in fact, this message (and hence all the randomness used in the protocol) is also optimal in the protocol of Feige et al. This improves on a previous result of Rajan et al. (ISIT 2016), which showed this optimality restricted to protocols where Alice and Bob are deterministic. Further, our result holds even if only a weak secrecy condition is required of the protocol.

Optimality of a Protocol by Feige-Kilian-Naor for Three-Party Secure Computation

The problem of three-party secure computation, where a function of private data of two parties is to be computed by a third party without revealing information beyond respective inputs or outputs is considered. New and better lower bounds on the amount of communication required between the parties to guarantee zero probability of error in the computation and achieve information-theoretic security are derived. Protocols are presented and proved to be optimal in some cases by showing that they achieve the improved lower bounds.

Lower bounds and optimal protocols for three-party secure computation

The question of how much communication is required between collaborating parties to compute a function of their data is of fundamental importance in the fields of theoretical computer science and information theory. In this work, the focus is on coming up with lower bounds on this. The information cost of a protocol is the amount of information the protocol reveals to Alice and Bob about each others inputs, and the information complexity of a function is the infimum of information costs over all valid protocols. For the amortized case, it is known that the optimal rate for the computation is equal to the information complexity. Exactly computing this information complexity is not straight forward however. In this work we lower bound information complexity for independent inputs in terms of the Wyner common information of a certain pair of random variables. We show a structural property for the optimal auxiliary random variable of Wyner common information and exploit this to exactly compute the Wyner common information in certain cases. The lower bound obtained through this technique is shown to be tight for a non-trivial example - equality (EQ) for the ternary alphabet. We also give an example to show that the lower bound may, in general, not be tight.

Sundara Rajan S

Papers

Lower bounds and optimal protocols for three-party secure computation

Lower bounds for interactive function computation via Wyner common information

Lower Bounds for Interactive Function Computation via Wyner Common Information