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: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

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 (US)
Title of host publicationWSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining
PublisherAssociation for Computing Machinery, Inc
Pages213-221
Number of pages9
ISBN (Electronic)9781450359405
DOIs
StatePublished - Jan 30 2019
Event12th ACM International Conference on Web Search and Data Mining, WSDM 2019 - Melbourne, Australia
Duration: Feb 11 2019Feb 15 2019

Publication series

NameWSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining

Conference

Conference12th ACM International Conference on Web Search and Data Mining, WSDM 2019
CountryAustralia
CityMelbourne
Period2/11/192/15/19

Fingerprint

History
Internet service providers
Websites
Internet
Communication
Experiments

Keywords

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

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software
  • Computer Science Applications

Cite this

Beigi, G., Guo, R., Nou, A., Zhang, Y., & Liu, H. (2019). Protecting user privacy: An approach for untraceable web browsing history and unambiguous user profiles. In WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining (pp. 213-221). (WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining). Association for Computing Machinery, Inc. https://doi.org/10.1145/3289600.3291026

Protecting user privacy : An approach for untraceable web browsing history and unambiguous user profiles. / Beigi, Ghazaleh; Guo, Ruocheng; Nou, Alexander; Zhang, Yanchao; Liu, Huan.

WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining. Association for Computing Machinery, Inc, 2019. p. 213-221 (WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Beigi, G, Guo, R, Nou, A, Zhang, Y & Liu, H 2019, Protecting user privacy: An approach for untraceable web browsing history and unambiguous user profiles. in WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining. WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining, Association for Computing Machinery, Inc, pp. 213-221, 12th ACM International Conference on Web Search and Data Mining, WSDM 2019, Melbourne, Australia, 2/11/19. https://doi.org/10.1145/3289600.3291026
Beigi G, Guo R, Nou A, Zhang Y, Liu H. Protecting user privacy: An approach for untraceable web browsing history and unambiguous user profiles. In WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining. Association for Computing Machinery, Inc. 2019. p. 213-221. (WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining). https://doi.org/10.1145/3289600.3291026
Beigi, Ghazaleh ; Guo, Ruocheng ; Nou, Alexander ; Zhang, Yanchao ; Liu, Huan. / Protecting user privacy : An approach for untraceable web browsing history and unambiguous user profiles. WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining. Association for Computing Machinery, Inc, 2019. pp. 213-221 (WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining).
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