Cryptographic framework for analyzing the privacy of recommender algorithms

Qiang Tang

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    2 Citations (Scopus)
    20 Downloads (Pure)

    Abstract

    Recommender algorithms are widely used, ranging from traditional Video on Demand to a wide variety of Web 2.0 services. Unfortunately, the related privacy concerns have not received much attention. In this paper, we study the privacy concerns associated with recommender algorithms and present a cryptographic security model to formulate the privacy properties. We propose two privacy-preserving content-based recommender algorithms and prove their properties. Moreover, we show the potential weakness in some existing collaborative filtering algorithms which claim to provide privacy protection.
    Original languageUndefined
    Title of host publicationInternational Conference on Collaboration Technologies and Systems, CTS 2012
    Place of PublicationUSA
    PublisherIEEE Computer Society
    Pages455-462
    Number of pages8
    ISBN (Print)978-1-4673-1381-0
    DOIs
    Publication statusPublished - 25 May 2012

    Publication series

    Name
    PublisherIEEE Computer Society

    Keywords

    • IR-81274
    • METIS-287976
    • Cryptography
    • EWI-22174
    • Privacy
    • SCS-Cybersecurity
    • Recommender algorithms

    Cite this

    Tang, Q. (2012). Cryptographic framework for analyzing the privacy of recommender algorithms. In International Conference on Collaboration Technologies and Systems, CTS 2012 (pp. 455-462). USA: IEEE Computer Society. https://doi.org/10.1109/CTS.2012.6261090
    Tang, Qiang. / Cryptographic framework for analyzing the privacy of recommender algorithms. International Conference on Collaboration Technologies and Systems, CTS 2012. USA : IEEE Computer Society, 2012. pp. 455-462
    @inproceedings{39268396b4964dfa926cc6ebe5107b03,
    title = "Cryptographic framework for analyzing the privacy of recommender algorithms",
    abstract = "Recommender algorithms are widely used, ranging from traditional Video on Demand to a wide variety of Web 2.0 services. Unfortunately, the related privacy concerns have not received much attention. In this paper, we study the privacy concerns associated with recommender algorithms and present a cryptographic security model to formulate the privacy properties. We propose two privacy-preserving content-based recommender algorithms and prove their properties. Moreover, we show the potential weakness in some existing collaborative filtering algorithms which claim to provide privacy protection.",
    keywords = "IR-81274, METIS-287976, Cryptography, EWI-22174, Privacy, SCS-Cybersecurity, Recommender algorithms",
    author = "Qiang Tang",
    note = "10.1109/CTS.2012.6261090",
    year = "2012",
    month = "5",
    day = "25",
    doi = "10.1109/CTS.2012.6261090",
    language = "Undefined",
    isbn = "978-1-4673-1381-0",
    publisher = "IEEE Computer Society",
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    booktitle = "International Conference on Collaboration Technologies and Systems, CTS 2012",
    address = "United States",

    }

    Tang, Q 2012, Cryptographic framework for analyzing the privacy of recommender algorithms. in International Conference on Collaboration Technologies and Systems, CTS 2012. IEEE Computer Society, USA, pp. 455-462. https://doi.org/10.1109/CTS.2012.6261090

    Cryptographic framework for analyzing the privacy of recommender algorithms. / Tang, Qiang.

    International Conference on Collaboration Technologies and Systems, CTS 2012. USA : IEEE Computer Society, 2012. p. 455-462.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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    AB - Recommender algorithms are widely used, ranging from traditional Video on Demand to a wide variety of Web 2.0 services. Unfortunately, the related privacy concerns have not received much attention. In this paper, we study the privacy concerns associated with recommender algorithms and present a cryptographic security model to formulate the privacy properties. We propose two privacy-preserving content-based recommender algorithms and prove their properties. Moreover, we show the potential weakness in some existing collaborative filtering algorithms which claim to provide privacy protection.

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    KW - METIS-287976

    KW - Cryptography

    KW - EWI-22174

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    KW - SCS-Cybersecurity

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    Tang Q. Cryptographic framework for analyzing the privacy of recommender algorithms. In International Conference on Collaboration Technologies and Systems, CTS 2012. USA: IEEE Computer Society. 2012. p. 455-462 https://doi.org/10.1109/CTS.2012.6261090