Privacy-preserving set intersection in outsourcing environments

We propose two privacy-preserving set intersection protocols in outsourcing environments. First, we propose a secure protocol (namely Protocol 1) for privacy-preserving set intersection using Mignotte´s secret sharing scheme. The data owner outsources a dataset A to w third-party service providers by Mignotte´s secret sharing scheme. Then, the user interacts with any k (k <; w) service providers to determine whether some elements of the user´s dataset B belong to the dataset A without disclosing any useful information to all parties. Furthermore, we also construct a privacy-preserving cardinality computation protocol (namely Protocol 2) of set intersection which has no disclosure about the result of set intersection by improving Protocol 1. In the semi-honest model, we prove the security of these protocols.