Behavioral biometrics based on mouse usage can be used to recognize one's identity, with special applications in anonymous Web browsing. Out of many features that describe browsing behavior, mouse clicks (or touches) as the most basic of navigation actions, provide a stable stream of behavioral data. The paper describes a method to recognize Web user according to three click features. The distancebased classification comparing cumulative distribution functions achieves high recognition accuracy even with hundreds of users.