The goal of Multi-Party Computation (MPC) is to perform an arbitrary computation in a distributed, private, and fault-tolerant way. For this purpose, a fixed set of n parties runs a protocol that tolerates an adversary corrupting a subset of the parties, preserving certain security guarantees like correctness, secrecy, robustness, and fairness. Corruptions can be either passive or active: A pas...

Anonymous blacklisting schemes allow online service providers to prevent future anonymous access by abusive users while preserving the privacy of all anonymous users (both abusive and non-abusive). The first scheme proposed for this purpose was Nymble, an extremely efficient scheme based only on symmetric primitives; however, Nymble relies on trusted third parties who can collude to de-anonymiz...

Privacy-preserving data publishing addresses the problem of disclosing sensitive data when mining for useful information. Among the existing privacy models, -differential privacy provides one of the strongest privacy guarantees. In this paper, we address the problem of private data publishing where data is horizontally divided among two parties over the same set of attributes. In particular, we...

In [1], Peikert proposed efficient and practical lattice-based protocols for key transport, encryption and authenticated key exchange. One of the main technical innovations of [1] is a reconciliation technique that allows two parties who ”approximately agree” on a secret value to reach exact agreement, a setting common to essentially all lattice-based encryption schemes. In [1], this reconcilia...

Most voting schemes rely on a number of authorities. If too many of these authorities are dishonest then voter privacy may be violated. To give stronger guarantees of voter privacy Kiayias and Yung [1] introduced the concept of elections with perfect ballot secrecy. In this type of election scheme it is guaranteed that the only thing revealed about voters’ choices is the result of the election,...

We propose a security model for open multi-agent systems. Given a user-defined task T , we generate a group of mobile agents which realise a common functionality that solves T . Those agents cooperate with each other and build an autonomous community. Using a scheme for secure distributed computations, this community is able to perform secure computations without requiring interaction with a tr...

In secure multi-party shuffling, multiple parties, each holding an input, want to agree on a random permutation of their inputs while keeping the permutation secret. This problem is important as a primitive in many privacy-preserving applications such as anonymous communication, location-based services, and electronic voting. Known techniques for solving this problem suffer from poor scalabilit...

We consider the problem of developing privacypreserving machine learning algorithms in a distributed multiparty setting. Here different parties own different parts of a data set, and the goal is to learn a classifier from the entire data set without any party revealing any information about the individual data points it owns. Pathak et al [7] recently proposed a solution to this problem in whic...

European citizens consider Radio Frequency Identification (RFID) to be the most intrusive technology of the past two decades. Safeguarding privacy requires specific action that needs attention of all parties involved. European citizens consider legal instruments to offer insufficient guarantees for safeguarding privacy. `Privacy by design ́ offers interesting opportunities to build in privacy gu...