Detecting and Analyzing Mouse Tracking in the Wild

Abstract

Nowadays, most websites collect personal information about their users in order to identify them and personalize their services. Among the tools used to that end, fingerprinting is one of the most advanced and precise methods, given the huge amount of features they can collect and combine to build a robust identifier of the user. Although many fingerprinting techniques have recently been studied in the literature, the use and prevalence of mouse tracking, a method that collects information about the computer pointer, is still unexplored in detail. In this work, we propose a new methodology to detect this tracking method and measure its actual usage on the top 80,000 most popular websites. Our results show that about 1.2% of the analyzed websites use some sort of mouse tracking, including some popular websites within the top-1k ranking.