Tracking Personal Identifiers Across the Web

User tracking has become de facto practice of the Web, however, our understanding of the scale and nature of this practice remains rudimentary. In this paper, we explore the connections amongst all parties of the Web, especially focusing on how trackers share user IDs. Using data collected from both browsing histories of 129 users and active experiments, we identify user-specific IDs that we suspect are used to track users. We find a significant amount of ID-sharing practices across different organisations providing various service categories. Our observations reveal that ID-sharing happens in a large scale regardless of the user profile size and profile condition such as logged-in and logged-out. We unexpectedly observe a higher number of ID-sharing domains when user is logged-out. We believe that our work reveals the huge gap between what is known about user tracking and what is done by this complex and important ecosystem.

[1]  Balachander Krishnamurthy,et al.  Best paper -- Follow the money: understanding economics of online aggregation and advertising , 2013, Internet Measurement Conference.

[2]  David Wetherall,et al.  Detecting and Defending Against Third-Party Tracking on the Web , 2012, NSDI.

[3]  Aaron Roth,et al.  Selling privacy at auction , 2015, Games Econ. Behav..

[4]  Steve Uhlig,et al.  The Rise of Panopticons: Examining Region-Specific Third-Party Web Tracking , 2014, TMA.

[5]  John C. Mitchell,et al.  Third-Party Web Tracking: Policy and Technology , 2012, 2012 IEEE Symposium on Security and Privacy.

[6]  Chris Jay Hoofnagle,et al.  Flash Cookies and Privacy II: Now with HTML5 and ETag Respawning , 2011 .

[7]  Mario Baldi,et al.  Identifying Personal Information in Internet Traffic , 2015, COSN.

[8]  Balachander Krishnamurthy,et al.  Privacy leakage vs . Protection measures : the growing disconnect , 2011 .

[9]  Balachander Krishnamurthy,et al.  WWW 2009 MADRID! Track: Security and Privacy / Session: Web Privacy Privacy Diffusion on the Web: A Longitudinal Perspective , 2022 .

[10]  Narseo Vallina-Rodriguez,et al.  Breaking for commercials: characterizing mobile advertising , 2012, Internet Measurement Conference.

[11]  Natasa Milic-Frayling,et al.  Network Analysis of Third Party Tracking: User Exposure to Tracking Cookies through Search , 2013, 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT).

[12]  Arvind Narayanan,et al.  The Web Never Forgets: Persistent Tracking Mechanisms in the Wild , 2014, CCS.

[13]  Gianluca Stringhini,et al.  The Dark Alleys of Madison Avenue: Understanding Malicious Advertisements , 2014, Internet Measurement Conference.