Blogs (61) >>
Wed 18 Jul 2018 11:24 - 11:40 at Winterthur - Session 1

Junior Submission
In recent years, web tracking has evolved as a major privacy concern on the Internet. Browser Fingerprinting could be considered as the most severe type of web tracking which takes advantage of web browsers inner features to obtain a unique fingerprint of users. Various methodologies have been proposed in order to combat browser fingerprinting. Most of them were based on static code analysis and the use of predefined blacklists. However, trackers are still able to fingerprint users by changing their techniques. As a result, previous methodologies which technically are signature-based cannot efficiently respond to new techniques. In this paper, we are proposing a comprehensive approach based on static analysis and machine learning to confront Browser Fingerprinting. Our proposed approach not only is able to identify unknown fingerprinting techniques, it also has a lower false positive rate.

Wed 18 Jul
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11:00 - 12:30: Session 1Doc Symposium at Winterthur
11:00 - 11:04
Day opening
Welcome
Doc Symposium
11:04 - 11:24
Talk
Lightning Talks
Doc Symposium
File Attached
11:24 - 11:40
Doctoral symposium paper
A Comprehensive Approach for Battling Browser Fingerprinting Based on Machine Learning
Doc Symposium
Mohammadreza AshouriUniversity of Potsdam, Germany
File Attached
11:40 - 11:56
Doctoral symposium paper
Leveraging Electromagnetic Side-Channel Attacks for Digital Forensics
Doc Symposium
Asanka SayakkaraUniversity College Dublin
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11:56 - 12:26
Talk
Looking ahead: what can we do during the PhD for a future career?
Doc Symposium
Mauro PezzeUniversità della Svizzera italiana (USI) and Università degli Studi di Milano Bicocca
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