A scalable multi-party protocol for privacy-preserving equality test

Abstract

Multi-party computation (MPC) is attractive for data owners who are interested in collaborating to execute queries without sharing their data. Since data owners in MPC do not trust each other, finding a secure protocol for privacy-preserving query processing is a major requirement for real world applications. This paper deals with equality test query among data of multiple data owners without revealing anyone's private data to others. In order to nicely scale with large size data, we show how communication and computation costs can be reduced via a bucketization technique. Our bucketization requires the use of a trusted third party (TTP) only at the beginning of the protocol execution. Experimental tests on horizontally distributed data show the effectiveness of our approach. © 2013 Springer-Verlag.