Privacy-preserving Top-k Dominating Queries in Distributed Multi-party Databases
Mahboob Qaosar, Kazi Md. Rokibul Alam, Chen Li, Yasuhiko Morimoto · 2019
In most of the business areas, many organizations are running similar trades and maintaining comparable databases. These organizations have noticed the importance of analyzing results obtained from the union of databases owned by different organizations. However, they do not want to disclose their contents to others since some of the contents are sensitive and private. Recently, preference-based queries have drawn massive attention in the database community. Particularly, the top-k dominating queries have been studied extensively, which selects the k objects that are better than other objects based on the `domination score'. In this paper, we have considered the top-k dominating queries on the combined databases of different organizations. We propose a secure framework for multi-party top-k dominating queries, where individual organizations do not need to expose their private databases to others. We analyze the privacy of our proposed framework and also evaluate its performance for various settings.