2018/11/22 by Ghazaleh Beigi, Ruocheng Guo, Beigi, Ghazaleh +7 · 1 citation
Computer Science · Social Sciences · #BitTorrent tracker #Computer science #Computer security #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Information privacy #Internet Traffic Analysis and Secure E-voting #Internet privacy #Privacy software #Privacy, Security, and Data Protection #Privacy-Preserving Technologies in Data #Social and Information Networks (cs.SI) #The Internet #Web navigation #Web page #Web service #World Wide Web
paper · pdf · doi:10.48550/arxiv.1811.09340
openalex publication_date 2018/11/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
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.