The Invisible Tracker: A Review of Browser Fingerprinting Mechanics, Applications, and Open Privacy Challenges

Abstract

This paper provides a comprehensive review of browser fingerprinting, an increasingly prevalent stateless tracking technique utilized in the wake of stricter privacy regulations and the deprecation of third-party cookies. The study dissects the technical mechanics of fingerprinting, exploring how information theory and Shannon entropy are applied to quantify browser uniqueness through both passive and active data extraction methods, including Canvas, WebGL, and hardware API exploitation. Furthermore, the paper examines the dual-use nature of the technology, highlighting its legitimate applications in cybersecurity for fraud prevention alongside its controversial use in pervasive cross-site behavioral profiling. The societal implications, such as the erosion of informed consent, the privacy paradox, and the risks of algorithmic discrimination based on socioeconomic inferences drawn from hardware telemetry, are critically analyzed. Finally, the article identifies key open privacy challenges, emphasizing the inherent invisibility of fingerprinting and the friction it introduces within modern consent-based regulatory frameworks.