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

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

1 被引用数 (Scopus)

抄録

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.

本文言語英語
ホスト出版物のタイトルProceedings - 2017 5th International Symposium on Computing and Networking, CANDAR 2017
出版社Institute of Electrical and Electronics Engineers Inc.
ページ533-536
ページ数4
ISBN(電子版)9781538620878
DOI
出版ステータス出版済み - 4 23 2018
イベント5th International Symposium on Computing and Networking, CANDAR 2017 - Aomori, 日本
継続期間: 11 19 201711 22 2017

出版物シリーズ

名前Proceedings - 2017 5th International Symposium on Computing and Networking, CANDAR 2017
2018-January

その他

その他5th International Symposium on Computing and Networking, CANDAR 2017
国/地域日本
CityAomori
Period11/19/1711/22/17

All Science Journal Classification (ASJC) codes

  • 人工知能
  • コンピュータ ネットワークおよび通信
  • ハードウェアとアーキテクチャ

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