# Fingerprinting the Fingerprinters: Learning to Detect Browser Fingerprinting Behaviors

arXiv: https://arxiv.org/abs/2008.04480 · HTML: https://mlsanity.com/paper/2008.04480/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Aug 2020.

## Built on by (most cited first, 8 of 8)

- [IsolateGPT: An Execution Isolation Architecture for LLM-Based Agentic Systems](https://mlsanity.com/paper/2403.04960/) (2024)
- [HARPO: Learning to Subvert Online Behavioral Advertising](https://mlsanity.com/paper/2111.05792/) (2021)
- [When AI Defeats Password Deception! A Deep Learning Framework to Distinguish Passwords and Honeywords](https://mlsanity.com/paper/2407.16964/) (2024)
- [PURL: Safe and Effective Sanitization of Link Decoration](https://mlsanity.com/paper/2308.03417/) (2023)
- [Targeted and Troublesome: Tracking and Advertising on Children's Websites](https://mlsanity.com/paper/2308.04887/) (2023)
- [Beyond the Request: Harnessing HTTP Response Headers for Cross-Browser Web Tracker Classification in an Imbalanced Setting](https://mlsanity.com/paper/2402.01240/) (2024)
- [SINBAD: Saliency-informed detection of breakage caused by ad blocking](https://mlsanity.com/paper/2405.05196/) (2024)
- [Fingerprinting and Tracing Shadows: The Development and Impact of Browser Fingerprinting on Digital Privacy](https://mlsanity.com/paper/2411.12045/) (2024)

## Abstract (arXiv)

Browser fingerprinting is an invasive and opaque stateless tracking technique. Browser vendors, academics, and standards bodies have long struggled to provide meaningful protections against browser fingerprinting that are both accurate and do not degrade user experience. We propose FP-Inspector, a machine learning based syntactic-semantic approach to accurately detect browser fingerprinting. We show that FP-Inspector performs well, allowing us to detect 26% more fingerprinting scripts than the state-of-the-art. We show that an API-level fingerprinting countermeasure, built upon FP-Inspector, helps reduce website breakage by a factor of 2. We use FP-Inspector to perform a measurement study of browser fingerprinting on top-100K websites. We find that browser fingerprinting is now present on more than 10% of the top-100K websites and over a quarter of the top-10K websites. We also discover previously unreported uses of JavaScript APIs by fingerprinting scripts suggesting that they are looking to exploit APIs in new and unexpected ways.