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Privacy protection of user profiles in online search via semantic randomization

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Abstract

Querying a search engine is one of the most frequent activities performed by Internet users. As queries are submitted, the server collects and aggregates them to build detailed user profiles. While user profiles are used to offer personalized search services, they may also be employed in behavioral targeting or, even worse, be transferred to third parties. Proactive protection of users' privacy in front of search engines has been tackled by submitting fake queries that aim at distorting the users' real profile. However, most approaches submit either random queries (which do not allow controlling the profile distortion) or queries constructed by following deterministic algorithms (which may be detected by aware search engines). In this paper, we propose a semantically grounded method to generate fake queries that (i) is driven by the privacy requirements of the user, (ii) submits the least number of fake queries needed to fulfill the requirements and (iii) creates queries in a non-deterministic way. Unlike related works, we accurately analyze and exploit the semantics underlying to user queries and their influence in the resulting profile. As a result, our approach offers more control—because users can tailor how their profile should be protected—and greater efficiency—because the desired protection is achieved with fewer fake queries. The experimental results on real query logs illustrate the benefits of our approach.

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Acknowledgements

This work was partly supported by the European Commission (Projects H2020-871042 SoBigData++ and H2020-101006879 MobiDataLab) the Spanish Government (Projects RTI2018-095094-B-C21 CONSENT and TIN2016-80250-R Sec-MCloud), the Norwegian Research Council (Project 308904 CLEANUP) and the Government of Catalonia (2017 SGR 705 and ICREA Acadèmia Prize to David Sánchez). The opinions expressed in this paper are those of the authors and do not necessarily reflect the views of UNESCO.

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Authors and Affiliations

  1. School of Engineering, University of Cadiz, Av. de la Universidad 10, 11519, Puerto Real, Cadiz, Spain

    Mercedes Rodriguez-Garcia

  2. Internet Interdisciplinary Institute (IN3), Universitat Oberta de Catalunya, Av. Carl Friedrich Gauss, 5, Parc Mediterrani de la Tecnologia, 08860, Castelldefels, Barcelona, Spain

    Montserrat Batet

  3. CYBERCAT-Center for Cybersecurity Research of Catalonia, UNESCO Chair in Data Privacy, Department of Computer Science and Mathematics, Universitat Rovira i Virgili, Av. Països Catalans, 26, 43007, Tarragona, Spain

    David Sánchez & Alexandre Viejo

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  1. Mercedes Rodriguez-Garcia
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  2. Montserrat Batet
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  4. Alexandre Viejo
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Correspondence to Mercedes Rodriguez-Garcia.

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Rodriguez-Garcia, M., Batet, M., Sánchez, D. et al. Privacy protection of user profiles in online search via semantic randomization. Knowl Inf Syst 63, 2455–2477 (2021). https://doi.org/10.1007/s10115-021-01597-x

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