%0 Conference Proceedings
%T Secure and Efficient k-NN Queries
%+ Rutgers, The State University of New Jersey [New Brunswick] (RU)
%+ Rutgers University [Camden]
%+ Lahore University of Management Sciences (LUMS)
%A Asif, Hafiz
%A Vaidya, Jaideep
%A Shafiq, Basit
%A Adam, Nabil
%Z Part 3: Private Queries and Aggregations
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 32th IFIP International Conference on ICT Systems Security and Privacy Protection (SEC)
%C Rome, Italy
%Y Sabrina De Capitani di Vimercati
%Y Fabio Martinelli
%I Springer International Publishing
%3 ICT Systems Security and Privacy Protection
%V AICT-502
%P 155-170
%8 2017-05-29
%D 2017
%R 10.1007/978-3-319-58469-0_11
%K k-NN queries
%K k-NN classification
%K Privacy
%K Distributed computation
%Z Computer Science [cs]Conference papers
%X Given the morass of available data, ranking and best match queries are often used to find records of interest. As such, k-NN queries, which give the k closest matches to a query point, are of particular interest, and have many applications. We study this problem in the context of the financial sector, wherein an investment portfolio database is queried for matching portfolios. Given the sensitivity of the information involved, our key contribution is to develop a secure k-NN computation protocol that can enable the computation k-NN queries in a distributed multi-party environment while taking domain semantics into account. The experimental results show that the proposed protocols are extremely efficient.
%G English
%Z TC 11
%2 https://inria.hal.science/hal-01649018/document
%2 https://inria.hal.science/hal-01649018/file/449885_1_En_11_Chapter.pdf
%L hal-01649018
%U https://inria.hal.science/hal-01649018
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC11
%~ IFIP-SEC
%~ IFIP-AICT-502