The rapid evolution of the digital landscape has transformed the Internet into an essential tool for communication, commerce, and information exchange. As users navigate this vast network, they leave behind digital traces, consisting of data points such as IP addresses, cookies, device information and browsing patterns. While these traces are often used to enhance user experience and personalize content, they also enable the identification and tracking of users across websites, raising concerns about user privacy and data security. The shift from digital ”footprints” to ”fingerprints” represents a significant change in tracking technology.
Traditional data collection methods (such as cookies) have become less effective due to increased user awareness and regulation, limiting their tracking capabilities. Consequently, more precise, device-level identification techniques have emerged. These methods utilize the unique characteristics of a user’s device to create a profile, enabling tracking across multiple sites and sessions.
Introduction
Conclusion
FINGER represents a focused and modular approach to addressing the growing challenge of browser fingerprinting. Building on the limitations identified in existing privacy tools, this extension introduces a behavior-based methodology that intercepts JavaScript property accesses and API calls in direct time, offering users visibility into fingerprinting attempts as they occur. Unlike traditional tracker blockers, FINGER does not rely on static filter lists or known domains.
Instead, it captures execution patterns that are indicative of fingerprinting, enabling the detection of both known and emerging techniques. This includes support for advanced vectors such as canvas rendering, audio context probing, font enumeration, and benchmark-based profiling. The extension’s modular architecture and open-source model further support community collaboration and rapid adaptation to new threats.
The results of our evaluation demonstrate that even browsers with built-in fingerprinting defenses remain vulnerable to sophisticated tracking methods. FINGER complements these native protections by providing a transparent, user-controllable layer of monitoring and analysis. As fingerprinting techniques continue to evolve, tools like FINGER will play a critical role in enabling researchers, developers, and privacy-conscious users to understand and respond to these threats. The project’s commitment to extensibility, transparency, and user empowerment positions it as a valuable contribution to the broader ecosystem of web privacy technologies.
Acknowledgement
This work is partially supported by the European Union/Next Generation through the Recovery and Resilience Facility (RRF), Investment RE-C05-i02: Interface Mission – CoLAB, with the following project code: 01/C05-i02/2022.P258.
Access Complete Publication
For an in-depth exploration of our findings and methodologies, download here
