Toward the attribution of Web behavior

As more people browse the Web to gather information, recognizing Web browsing behavior signatures can replace or complement keystroke authentication where authentication is defined as the capability of identifying an individual within a set of individuals. We claim that recurring temporal patterns of Web site visits can help identify an individual of interest and, more generally, categorize Web browsing behavior. Furthermore, just like keystroke authentication, attribution of Web behavior is not obtrusive and has applications in cyberwarfare as a new biometric technique. In this paper we describe some exploratory work and preliminary comparative results of machine learning techniques applicable to the attribution of Web browsing behavior problem.