Unconditionally Secure Computation with Reduced Interaction

We study the question of how much interaction is needed for unconditionally secure multiparty computation. We first consider the number of messages that need to be sent to compute a Boolean function with semi-honest security, where all $n$ parties learn the result. We consider two classes of functions called $t$-difficult and $t$-very difficult functions, here $t$ refers to the number of corrupted players. One class is contained in the other. For instance, the AND of an input bit from each player is $t$-very difficult while the XOR is $t$-difficult but not $t$-very difficult. We show lower bounds on the message complexity of both types of functions, considering two notions of message complexity called conservative and liberal, where the conservative one is the more standard one. In all cases the bounds are $\Omega(nt)$. We also show upper bounds for $t=1$ and functions in deterministic log-space, as well as a stronger upper bound for the XOR function. This matches the lower bound for conservative complexity, so we find that the conservative message complexity of $1$-very difficult functions in deterministic log space is $2n$, while the conservative message complexity for XOR (and $t=1$) is $2n-1$. Next, we consider round complexity. It is a long-standing open problem to determine whether all efficiently computable functions can also be efficiently computed in constant-round with {\em unconditional} security. Motivated by this, we consider the question of whether we can compute any function securely, while minimizing the interaction of {\em some of} the players? And if so, how many players can this apply to? Note that we still want the standard security guarantees (correctness, privacy, termination) and we consider the standard communication model with secure point-to-point channels. We answer the questions as follows: for passive security, with $n=2t+1$ players and $t$ corruptions, up to $t$ players can have minimal interaction, i.e., they send 1 message in the first round to each of the $t+1$ remaining players and receive one message from each of them in the last round. Using our result on message complexity, we show that this is (unconditionally) optimal. For malicious security with $n=3t+1$ players and $t$ corruptions, up to $t$ players can have minimal interaction, and we show that this is also optimal

Choice logics and their computational properties

Qualitative Choice Logic (QCL) and Conjunctive Choice Logic (CCL) are formalisms for preference handling, with especially QCL being well established in the field of AI. So far, analyses of these logics need to be done on a case-by-case basis, albeit they share several common features. This calls for a more general choice logic framework, with QCL and CCL as well as some of their derivatives being particular instantiations. We provide such a framework, which allows us, on the one hand, to easily define new choice logics and, on the other hand, to examine properties of different choice logics in a uniform setting. In particular, we investigate strong equivalence, a core concept in non-classical logics for understanding formula simplification, and computational complexity. Our analysis also yields new results for QCL and CCL. For example, we show that the main reasoning task regarding preferred models is $\Theta^p_2$-complete for QCL and CCL, while being $\Delta^p_2$-complete for a newly introduced choice logic.Comment: This is an extended version of a paper of the same name to be published at IJCAI 202