The lack of privacy protection for Internet users has been identified
as a major problem in modern web browsers.  Despite potentially high
risk of identification by typing patterns, this topic has received
little attention in both the research and general community.  In this
paper we present a simple but efficient statistical detection model
for constructing identity from their typing patterns.  Extensive
experiments are conducted to justify the accuracy of our model.  Using
this model, online adversaries could uncover the identity of Web users
even if they are using anonymizing services.  Our goal is to raise
awareness of this privacy risk to general Internet users and encourage
countermeasures in future implementations of anonymous browsing
techniques.