[B]y observing how people navigate around a site over a number of sessions, an e-commerce company could distinguish between two anonymous surfers. That could have important implications in preventing fraud: if someone signed in with an existing user's logon, but their clickprint differed, that might be an indication that their ID had been stolen.

Your mouse is leaving tracks all over the Net

By observing the online behavior of a Web surfer for as few as three sessions on the Internet, researchers say they can identify that person by his or her "clickprint." A clickprint is a "unique pattern of Web-surfing behavior based on actions such as the number of pages viewed per session, the number of minutes spent on each Web page, the time or day of the week the page is visited, and so on," said a report last week from the Wharton School at the University of Pennsylvania

We address the question of whether humans have unique signatures — or clickprints — when they browse the Web. The importance of being able to answer this can be significant given applications to electronic commerce in general and in particular online fraud detection, a major problem in electronic commerce costing the economy billions of dollars annually. In this paper we present a data mining approach to answer this "unique clickprint determination problem".