Privacy-preserving recommendations in context-aware mobile environments

Nikolaos Polatidis, Christos K. Georgiadis, Elias Pimenidis, Emmanouil Stiakakis

    Research output: Contribution to journalArticlepeer-review


    This paper aims to address privacy concerns that arise from the use of mobile recommender systems when processing contextual information relating to the user. Mobile recommender systems aim to solve the information overload problem by recommending products or services to users of Web services on mobile devices, such as smartphones or tablets, at any given point in time and in any possible location. They use recommendation methods, such as collaborative filtering or content-based filtering and use a considerable amount of contextual information to provide relevant recommendations. However, because of privacy concerns, users are not willing to provide the required personal information that would allow their views to be recorded and make these systems usable.

    This work is focused on user privacy by providing a method for context privacy-preservation and privacy protection at user interface level. Thus, a set of algorithms that are part of the method has been designed with privacy protection in mind, which is done by using realistic dummy parameter creation. To demonstrate the applicability of the method, a relevant context-aware data set has been used to run performance and usability tests.

    The proposed method has been experimentally evaluated using performance and usability evaluation tests and is shown that with a small decrease in terms of performance, user privacy can be protected.

    This is a novel research paper that proposed a method for protecting the privacy of mobile recommender systems users when context parameters are used.
    Original languageEnglish
    Pages (from-to)62-79
    JournalInformation and Computer Security
    Issue number1
    Publication statusPublished - 13 Mar 2017


    Dive into the research topics of 'Privacy-preserving recommendations in context-aware mobile environments'. Together they form a unique fingerprint.

    Cite this