SoK: Advances and Open Problems in Web Tracking
cs.CR, cs.CY, cs.NI
Submitted: 2025-06-16
Updated: 2026-09-16
Comments: Extended Version is available at: https://github.com/privacysandstorm/sok-advances-open-problems-web-tracking
Code: https://github.com/privacysandstorm/sok-advances-open-problems-web-tracking
Project page: https://privacycg.github.io/storage-partitioning
License: http://creativecommons.org/licenses/by/4.0/
The gist: Web tracking is a pervasive and opaque practice that enables personalized advertising, retargeting, and conversion tracking.
Terminology
Abstract
Web tracking is a pervasive and opaque practice that enables personalized advertising, retargeting, and conversion tracking. Over time, it has evolved into a sophisticated and invasive ecosystem, employing increasingly complex techniques to monitor and profile users across the web. The research community has a long track record of analyzing new web tracking techniques, designing and evaluating the effectiveness of countermeasures, and assessing compliance with privacy regulations. Despite a substantial body of work on web tracking, the literature remains fragmented across distinctly scoped studies, making it difficult to identify overarching trends, connect new but related techniques, and identify research gaps in the field. Today, web tracking is undergoing a transformation, driven by fundamental shifts in the advertising industry, the adoption of anti-tracking countermeasures by browsers, and the growing enforcement of emerging privacy regulations. This Systematization of Knowledge (SoK) aims to consolidate and synthesize this wide-ranging research, offering a comprehensive overview of the technical mechanisms, countermeasures, and regulations that shape the modern and rapidly evolving web tracking landscape. This SoK also highlights open challenges and outlines directions for future research.
Sources
- PURL: Safe and Effective Sanitization of Link Decoration
- Measuring Compliance of Consent Revocation on the Web
- Big Help or Big Brother? Auditing Tracking, Profiling, and Personalization in Generative AI Assistants
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