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Protecting user privacy: An approach for untraceable web browsing history and unambiguous user profiles

  • Ghazaleh Beigi
  • , Ruocheng Guo
  • , Alexander Nou
  • , Yanchao Zhang
  • , Huan Liu

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

The overturning of the Internet Privacy Rules by the Federal Communications Commissions (FCC) in late March 2017 allows Internet Service Providers (ISPs) to collect, share and sell their customers' Web browsing data without their consent. With third-party trackers embedded on Web pages, this new rule has put user privacy under more risk. The need arises for users on their own to protect their Web browsing history from any potential adversaries. Although some available solutions such as Tor, VPN, and HTTPS can help users conceal their online activities, their use can also significantly hamper personalized online services, i.e., degraded utility. In this paper, we design an effective Web browsing history anonymization scheme, PBooster, aiming to protect users' privacy while retaining the utility of their Web browsing history. The proposed model pollutes users' Web browsing history by automatically inferring how many and what links should be added to the history while addressing the utility-privacy trade-off challenge. We conduct experiments to validate the quality of the manipulated Web browsing history and examine the robustness of the proposed approach for user privacy protection.
Original languageEnglish
Title of host publicationWSDM'19
Subtitle of host publicationProceedings of the Twelfth ACM International Conference on Web Search and Data Mining
PublisherAssociation for Computing Machinery
Pages213-221
ISBN (Electronic)9781450359405
DOIs
Publication statusPublished - 2019
Externally publishedYes
Event12th ACM International Conference on Web Search and Data Mining, WSDM 2019 - Melbourne, Australia
Duration: 11 Feb 201915 Feb 2019

Publication series

NameWSDM - Proceedings of the ACM International Conference on Web Search and Data Mining

Conference

Conference12th ACM International Conference on Web Search and Data Mining, WSDM 2019
PlaceAustralia
CityMelbourne
Period11/02/1915/02/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Research Keywords

  • Privacy
  • Trade-off
  • Utility
  • Web browsing history anonymization

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