In the setting of secure multiparty computation, a set of mutually distrustful parties carry out a joint computation of their inputs, without revealing anything but the output. Over recent years, there has been tremendous progress towards making secure computation practical, with great success in the two-party case. In contrast, in the multiparty case, progress has been much slower, even for th...

The deployment of Genome-wide association studies (GWASs) requires genomic information of a large population to produce reliable results. This raises significant privacy concerns, making people hesitate to contribute their genetic information to such studies. We propose two provably secure solutions to address this challenge: (1) a somewhat homomorphic encryption approach, and (2) a secure mult...

In this paper, we propose a comparison of two seemingly similar problems, i.e., secure multiparty computation and fair exchange. However, if these two problems appear to bear a lot in common, they come from fields that differ greatly in the way the problems are described and approached, i.e., the fields of modern cryptography and distributed systems respectively. In that regard, straightforward...

We propose a secure voting protocol for score-based rules, where independent talliers perform the tallying procedure. The outputs winning candidate(s) while preserving privacy of voters and secrecy ballots. It offers perfect secrecy, in sense that apart from desired output, all other information – ballots, intermediate values, final scores received by each candidates is not disclosed to any par...

Secure set-intersection computation is one of important problems in secure multiparty computation with various applications. We propose a general construction for secure 2-party set-intersection computation based-on anonymous IBE (identity-based encryption) scheme and its user private-keys blind generation techniques. Compared with related works, this construction is provably GUC(generalized un...

We initiate a study of garbled circuits that contain both Boolean and arithmetic gatesin secure multiparty computation. In particular, we incorporate the garbling gadgets for arithmeticcircuits recently presented by Ball, Malkin, and Rosulek (ACM CCS 2016) into the multiparty garblingparadigm initially introduced by Beaver, Micali, and Rogaway (STOC ’90). This is the first work that...

Secure sum computation of private data inputs is an interesting example of Secure Multiparty Computation (SMC) which has attracted many researchers to devise secure protocols with lower probability of data leakage. In this paper, we provide a novel protocol to compute the sum of individual data inputs with zero probability of data leakage when two neighbor parties collude to know the data of a ...

In recent years, deep learning has become an increasingly popular approach to modelling data due its ability detect abstract underlying patterns in data. Its practical applications have been limited, however, by privacy concerns, restricting use major sectors such as healthcare and banking. Secure multiparty computation (MPC) is a scheme which allows multiple parties perform joint computations ...