Peer-to-Peer Secure Multi-party Numerical Computation

We propose an efficient framework for enabling secure multi-party numerical computations in a Peer-to-Peer network. This problem arises in a range of applications such as collaborative filtering, distributed computation of trust and reputation, monitoring and numerous other tasks, where the computing nodes would like to preserve the privacy of their inputs while performing a joint computation of a certain function. Although there is a rich literature in the field of distributed systems security concerning secure multi-party computation, in practice it is hard to deploy those methods in very large scale Peer-to-Peer networks. In this work, we examine several possible approaches and discuss their feasibility. Among the possible approaches, we identify a single approach which is both scalable and theoretically secure. An additional novel contribution is that we show how to compute the neighborhood based collaborative filtering, a state-of-the-art collaborative filtering algorithm, w...

• Type: Conference
• Year: 2008
• Where: P2P
• Authors: Danny Bickson, Danny Dolev, Genia Bezman, Benny Pinkas
• Keywords: Large Scale, P2P 2008, Peer-to-Peer Computing, Peer-to-peer Network, Secure Multi-party Computation