For good or ill, what users do on the web is tracked. Banks track users as an authentication technique, to offer their customers enhanced security protection. Retailers track customers and potential customers in order to deliver personalized service tailored to their tastes and needs.
The method commonly used for tracking is called web fingerprinting. Web fingerprinting is a way of collecting information that can be used to fully or partially identify a given user, even when cookies are disabled.
Such techniques have been evolving quickly. Yet, the most advanced and commonly used methods track users in a single browser only.
Now a team of researchers led by Yinzhi Cao, assistant professor computer science and engineering—and including graduate student Song Li of Lehigh and Erik Wijmans of Washington University in St. Louis—has developed the first cross-browser fingerprinting technique to use machine-level features to identify users.
Read more at Lehigh University