Canvas fingerprinting is a technique used to surreptitiously—no user consent needed!—track users across the web.

The technique takes advantage of how different computers will draw the same image (on the canvas) differently, depending on the computer’s software and hardware characteristics. We conducted a large-scale study analyzing canvas fingerprinting on approximately half a million websites listed on Alexa Top Sites. We then created a “smart” tracking blocker which leverages a machine learning classifier to distinguish between images drawn for fingerprinting (i.e., tracking) and images drawn for non-fingerprinting (i.e., non-tracking).

The full paper, appearing in the 21st Privacy Enhancing Technologies Symposium, is available at the link below. This website summarizes a few of our high-level findings.



3Canvas in the Wild

4Machine Learning Models