When datasets are distributed on different sources, finding out their intersection while preserving the privacy of the datasets is a widely required task. In this paper, we addre...
With the growing demand of databases outsourcing and its security concerns, we investigate privacy-preserving set intersection in a distributed scenario. We propose a one-round pr...
We propose a more efficient privacy preserving set intersection protocol which improves the previously known result by a factor of O(N) in both the computation and communication c...
Companies, organizations, and individuals often wish to share information to realize valuable social and economic goals. Unfortunately, privacy concerns often stand in the way of ...
Currently, many privacy-preserving data mining (PPDM) algorithms assume the semi-honest model and/or malicious model of multi-party interaction. However, both models are far from ...