The Complex Third-Party Tracking Ecosystem: A Multi-Dimensional Perspective
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The third-party tracking ecosystem continuously evolves in scope, therefore, understanding of it is at best elusive. In this thesis, we investigate this complex ecosystem from three dimen-sions. Firstly, we examine third-party trackers from a geographical perspective. We observe a non-uniform presence of local third-party trackers between regions and countries within re-gions, with some trackers focusing on specific regions and countries. Secondly, we focus on how trackers share user-specific identifiers (IDs). We identify user-specific IDs that we suspect are used to track users. We find a significant amount of ID-sharing practices across different organ-isations providing various service categories. Our observations reveal that ID-sharing happens at a large scale regardless of the user profile size and profile condition such as logged-in and logged-out. Finally, we quantify the effect of tracker-blockers, a popular option for the users to protect their privacy, on the page-load performance. The effect of such tools on the over-all user browsing experience is questionable as the blockage of trackers can disrupt the general website loading process. The tracker-blockers we studied have a considerable negative effect on page-load performance. Unexpectedly, we find that even highly popular websites are negatively affected. This thesis points to significant gaps in our knowledge about the inner workings of this complex ecosystem. Moreover, it highlights some of the challenges that we face when attempting to preserve user’s privacy by using tracker-blockers.
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