# My Mouse, My Rules: Privacy Issues of Behavioral User Profiling via Mouse Tracking

arXiv: https://arxiv.org/abs/2101.09087 · HTML: https://mlsanity.com/paper/2101.09087/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Jan 2021.

## Built on by (most cited first, 2 of 2)

- [A Versatile Dataset of Mouse and Eye Movements on Search Engine Results Pages](https://mlsanity.com/paper/2507.08003/) (2025)
- [JIR-Arena: The First Benchmark Dataset for Just-in-time Information Recommendation](https://mlsanity.com/paper/2505.13550/) (2025)

## Abstract (arXiv)

This paper aims to stir debate about a disconcerting privacy issue on web browsing that could easily emerge because of unethical practices and uncontrolled use of technology. We demonstrate how straightforward is to capture behavioral data about the users at scale, by unobtrusively tracking their mouse cursor movements, and predict user's demographics information with reasonable accuracy using five lines of code. Based on our results, we propose an adversarial method to mitigate user profiling techniques that make use of mouse cursor tracking, such as the recurrent neural net we analyze in this paper. We also release our data and a web browser extension that implements our adversarial method, so that others can benefit from this work in practice.