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10.1109/ICDCS.2008.79guideproceedingsArticle/Chapter ViewAbstractPublication PagesConference Proceedingsacm-pubtype
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Efficient Privacy-Preserving k-Nearest Neighbor Search

Published:17 June 2008Publication History

ABSTRACT

We give efficient protocols for secure and private k-nearest neighbor (k-NN) search, when the data is distributed between two parties who want to cooperatively compute the answers without revealing to each other their private data. Our protocol for the single-step k-NN search is provably secure and has linear computation and communication complexity. Previous work on this problem had a quadratic complexity, and also leaked information about the parties' inputs. We adapt our techniquesto also solve the general multi-step k-NN search, and describe a specific embodiment of it for the case of sequence data. The protocols and correctness proofs can be extended to suit other privacy-preserving data mining tasks, such as classification and outlier detection.

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  • Published in

    cover image Guide Proceedings
    ICDCS '08: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems
    June 2008
    886 pages
    ISBN:9780769531724

    Publisher

    IEEE Computer Society

    United States

    Publication History

    • Published: 17 June 2008

    Qualifiers

    • Article