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

Abstract

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.

arXiv commentIn Proceedings of the 2021 ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR '21), March 14-19, 2021, Canberra, Australia

References in corpus (6)

• XRay: Enhancing the Web's Transparency with Differential Correlation
• I Always Feel Like Somebody's Watching Me. Measuring Online Behavioural Advertising
• MyAdChoices: Bringing Transparency and Control to Online Advertising
• Most Websites Don't Need to Vibrate: A Cost-Benefit Approach to Improving Browser Security
• A Price-Per-Attention Auction Scheme Using Mouse Cursor Information
• Who's Tracking Sensitive Domains?

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