Privacy-Preserving Content-Based Recommender System

Z. Erkin, M. Beye, T. Veugen, R.L. Lagendijk

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

    17 Citations (Scopus)
    54 Downloads (Pure)


    By offering personalized content to users, recommender systems have become a vital tool in e-commerce and online media applications. Content-based algorithms recommend items or products to users, that are most similar to those previously purchased or consumed. Unfortunately, collecting and storing ratings, on which content-based methods rely, also poses a serious privacy risk for the customers: ratings may be very personal or revealing, and thus highly privacy sensitive. Service providers could process the collected rating data for other purposes, sell them to third parties or fail to provide adequate physical security. In this paper, we propose technological mechanisms to protect the privacy of individuals in a recommender system. Our proposal is founded on homomorphic encryption, which is used to obscure the private rating information of the customers from the service provider. While the user’s privacy is respected by the service provider, by generating recommendations using encrypted customer ratings, the service provider’s commercially valuable item-item similarities are protected against curious entities, in turn. Our proposal explores simple and efficient cryptographic techniques to generate private recommendations using a server-client model, which neither relies on (trusted) third parties, nor requires interaction with peer users. The main strength of our contribution lies in providing a highly efficient solution without resorting to unrealistic assumptions.
    Original languageEnglish
    Title of host publicationProceedings of the 14th ACM workshop on Multimedia and Security
    Place of PublicationNew York
    PublisherAssociation for Computing Machinery
    Number of pages8
    ISBN (Print)978-1-4503-1417-6
    Publication statusPublished - 2012
    Event14th ACM workshop on Multimedia and Security, MM&Sec 2012 - Coventry, United Kingdom
    Duration: 6 Sept 20127 Sept 2012
    Conference number: 14


    Workshop14th ACM workshop on Multimedia and Security, MM&Sec 2012
    Abbreviated titleMM&Sec
    Country/TerritoryUnited Kingdom


    Dive into the research topics of 'Privacy-Preserving Content-Based Recommender System'. Together they form a unique fingerprint.

    Cite this