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 language | English (US) |
|---|---|
| Title of host publication | WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 213-221 |
| Number of pages | 9 |
| ISBN (Electronic) | 9781450359405 |
| DOIs | |
| State | Published - Jan 30 2019 |
| Event | 12th ACM International Conference on Web Search and Data Mining, WSDM 2019 - Melbourne, Australia Duration: Feb 11 2019 → Feb 15 2019 |
Publication series
| Name | WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining |
|---|
Conference
| Conference | 12th ACM International Conference on Web Search and Data Mining, WSDM 2019 |
|---|---|
| Country | Australia |
| City | Melbourne |
| Period | 2/11/19 → 2/15/19 |
Fingerprint
Keywords
- Privacy
- Trade-off
- Utility
- Web browsing history anonymization
ASJC Scopus subject areas
- Computer Networks and Communications
- Software
- Computer Science Applications
Cite this
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 proceeding › Conference contribution
}
TY - GEN
T1 - Protecting user privacy
T2 - An approach for untraceable web browsing history and unambiguous user profiles
AU - Beigi, Ghazaleh
AU - Guo, Ruocheng
AU - Nou, Alexander
AU - Zhang, Yanchao
AU - Liu, Huan
PY - 2019/1/30
Y1 - 2019/1/30
N2 - 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.
AB - 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.
KW - Privacy
KW - Trade-off
KW - Utility
KW - Web browsing history anonymization
UR - http://www.scopus.com/inward/record.url?scp=85061705239&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85061705239&partnerID=8YFLogxK
U2 - 10.1145/3289600.3291026
DO - 10.1145/3289600.3291026
M3 - Conference contribution
AN - SCOPUS:85061705239
T3 - WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining
SP - 213
EP - 221
BT - WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining
PB - Association for Computing Machinery, Inc
ER -