Effectively Protect Your Privacy: Enabling Flexible Privacy Control on Web Tracking

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

1 Citation (Scopus)

Abstract

Third-party tracking, which can collect the users' privacy when users are surfing the Internet, has garnered much attention. Nowadays tracker-blocking tools often use a ruleset based on the domains and elements that need to be blocked. This results in blocking all access tracking, even though the website shows no sign about tracking users' privacy. And what's more, although the tracker-blocking tools try their best to block all the third-party tracking, not all the users dislike the advertisement. Some of them think if their privacy is fine, it's all right to accept advertisements. In this paper, we present a novel framework by using Word2Vec to block third-party tracking. Our goal is to create more flexible and well-developed ruleset that can help users to protect their privacy according to their needs. Instead of blocking all access tracking, we decide to pay more attention to the websites that have a strong probability to collect the users' privacy. We use Word2Vec to classify the websites, and our results show that after using our framework, the error rate drops from 71% to 24%. We believe it brings the new blood into the field of web privacy by providing not only the new third-party tracking tool but also a novel way of thinking about how to block the third-party tracking.

Original languageEnglish
Title of host publicationProceedings - 2017 5th International Symposium on Computing and Networking, CANDAR 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages533-536
Number of pages4
ISBN (Electronic)9781538620878
DOIs
Publication statusPublished - Apr 23 2018
Event5th International Symposium on Computing and Networking, CANDAR 2017 - Aomori, Japan
Duration: Nov 19 2017Nov 22 2017

Publication series

NameProceedings - 2017 5th International Symposium on Computing and Networking, CANDAR 2017
Volume2018-January

Other

Other5th International Symposium on Computing and Networking, CANDAR 2017
CountryJapan
CityAomori
Period11/19/1711/22/17

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture

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    Yu, S., Vargas, D. V., & Sakurai, K. (2018). Effectively Protect Your Privacy: Enabling Flexible Privacy Control on Web Tracking. In Proceedings - 2017 5th International Symposium on Computing and Networking, CANDAR 2017 (pp. 533-536). (Proceedings - 2017 5th International Symposium on Computing and Networking, CANDAR 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CANDAR.2017.26