SoK: After Decades of Web Tracker Detection, What's Next?
For researchers and practitioners in web privacy, this work provides a structured overview and critical assessment of the field, highlighting reproducibility issues and guiding future work.
This SoK paper presents a comprehensive meta-science study on web tracker detection, systematizing 59 primary studies from 832 papers, proposing a taxonomy, and identifying open research gaps and recommendations for future research.
Web tracking is an omnipresent phenomenon in today's web, affecting users in their day-to-day lives. Filter lists and blockers were invented to detect trackers and to protect users. Due to limitations of said tools, researchers developed web tracker detectors to replace them. No review constructed a universal perspective and classification of web tracker detectors until now. Past reviews focused either on the field as a whole or on web tracking techniques. In this SoK paper, we present the most comprehensive meta-science study on web tracker detection by systematizing and synthesizing the available knowledge. We conduct a systematic review, resulting in 59 primary and 16 supplementary studies out of a corpus of 832 papers. Based on these findings we suggest a taxonomy, observe and evaluate trends, propose open research gaps, and recommendations with which we aim to lay the foundations for future web tracker detection research. In addition, we conduct a limited reproducibility study to assess the validity of past studies and highlight emerging problems in this field.