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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, the authors present a simple but efficient statistical detection model for constructing users' identity from their typing patterns. Extensive experiments are conducted to justify the accuracy of their model. Using this model, online adversaries could uncover the identity of Web users even if they are using anonymizing services.
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