SoK: After Decades of Web Tracker Detection, What's Next?

TL;DR

This paper provides a comprehensive review and classification of web tracker detection methods, analyzing past research, identifying gaps, and proposing directions for future work.

Contribution

It offers the first systematic taxonomy and synthesis of web tracker detectors, along with a reproducibility study and research recommendations.

Findings

Developed a taxonomy of web tracker detection techniques.

Analyzed trends and identified open research gaps.

Assessed the validity of past studies through reproducibility analysis.

Abstract

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.