Privacy-Preserving Top-k Query Processing in Distributed Systems
Abstract
We consider a distributed system that stores user sensitive data across multiple nodes. In this context, we address the problem of privacy-preserving top-k query processing. We propose a novel system, called SD-TOPK, that is able to evaluate top-k queries over encrypted distributed data without needing to decrypt the data in the nodes where they are stored. We implemented and evaluated our system over synthetic and real databases. The results show excellent performance for SD-TOPK compared to baseline approaches.
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