TY - GEN
T1 - Effectively Protect Your Privacy
T2 - 5th International Symposium on Computing and Networking, CANDAR 2017
AU - Yu, Shiqian
AU - Vargas, Danilo Vasconcellos
AU - Sakurai, Kouichi
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85050355266&partnerID=8YFLogxK
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U2 - 10.1109/CANDAR.2017.26
DO - 10.1109/CANDAR.2017.26
M3 - Conference contribution
AN - SCOPUS:85050355266
T3 - Proceedings - 2017 5th International Symposium on Computing and Networking, CANDAR 2017
SP - 533
EP - 536
BT - Proceedings - 2017 5th International Symposium on Computing and Networking, CANDAR 2017
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 19 November 2017 through 22 November 2017
ER -