We present the first general protocol for secure multiparty computation in which the total amount of work required by n players to compute a function f grows only polylogarithmically with n (ignoring an additive term that depends on n but not on the complexity of f). Moreover, the protocol is also nearly optimal in terms of resilience, providing computational security against an active, adaptiv...

We introduce the notion of covert privacy for secret-sharingbased secure multiparty computation (SMC) protocols. We show how covertly or actively private SMC protocols, together with recently introduced verifiable protocols allow the construction of SMC protocols secure against active adversaries. For certain computational problems, the relative overhead of our protocols, when compared to proto...

We present the first black-box construction of a secure multiparty computation protocol that satisfies a meaningful notion of concurrent security in the plain model (without any set-up, and without assuming an honest majority). Moreover, our protocol relies on the minimal assumption of the existence of a semi-honest OT protocol, and our security notion “UC with super-polynomial helpers” (Canett...

We present new results in the framework of secure multiparty computation based on homomorphic threshold cryptosystems. We introduce the conditional gate as a special type of multiplication gate that can be realized in a surprisingly simple and efficient way using just standard homomorphic threshold ElGamal encryption. As addition gates are essentially for free, the conditional gate not only all...

A new promising direction in cryptography, started almost twenty years ago, is the field of Secure Multiparty Computation. In this scenario a set of players want to compute some functions on their inputs, but they don’t trust each other so they don’t want to disclose their inputs to each other. The purpose of this thesis is to investigate the Oblivious Transfer primitive, one of the fundamental...

The traditional paradigm in machine learning has been that given a data set, the goal is to learn a target function or decision model (such as a classifier) from it. Many techniques in data mining and machine learning follow a gradient descent paradigm in the iterative process of discovering this target function or decision model. For instance, Linear regression can be resolved through a gradie...

Cryptographic protocols with adaptive security ensure that security holds against an adversary who can dynamically determine which parties to corrupt as the protocol progresses—or even after the protocol is finished. In the setting where all parties may potentially be corrupted, and secure erasure is not assumed, it has been a long-standing open question to design secure-computation protocols w...

A reputation system for a set of entities is essentially a list of scores that provides a measure of the reliability of each entity in the set. The score given to an entity can be interpreted (and in the reputation system literature it often is [12]) as the probability that an entity will behave honestly. In this paper, we ask whether or not it is possible to utilize reputation systems for carr...

Oblivious transfer (OT) is an essential building block for secure multiparty computation when there is no honest majority. In this setting, current protocols for n ≥ 3 parties require each pair of parties to engage in a single OT for each gate in the circuit being evaluated. Since implementing OT typically requires expensive public-key operations (alternatively, expensive setup or physical infr...

A protocol for computing a functionality is secure if an adversary in this protocol cannot cause more harm than in an ideal computation, where parties give their inputs to a trusted party which returns the output of the functionality to all parties. In particular, in the ideal model such computation is fair – all parties get the output. Cleve (STOC 1986) proved that, in general, fairness is not...