@article{chen_yu_chirkova_2016, title={Privacy-Preserving Two-Party Skyline Queries Over Horizontally Partitioned Data}, volume={9895}, ISBN={["978-3-319-45930-1"]}, ISSN={["1611-3349"]}, DOI={10.1007/978-3-319-45931-8_12}, abstractNote={Skyline queries are an important type of multi-criteria analysis with diverse applications in practice (e.g., personalized services and intelligent transport systems). In this paper, we study how to answer skyline queries efficiently and in a privacy-preserving way when the data are sensitive and distributedly owned by multiple parties. We adopt the classical honest-but-curious attack model, and design a suite of efficient protocols for skyline queries over horizontally partitioned data. We analyze in detail the efficiency of each of the proposed protocols as well as their privacy guarantees.}, journal={INFORMATION SECURITY THEORY AND PRACTICE, WISTP 2016}, author={Chen, Ling and Yu, Ting and Chirkova, Rada}, year={2016}, pages={187–203} }