Faced with both identity theft and the theft of means of authentication, users of digital services are starting to look rather suspiciously at online systems. The behavior is made up of a series of observable actions of an Internet user and, taken as a whole, the most frequent of these actions amount to habit. Habit and reputation oer ways of recognizing the user. The introduction of an implicit means of authenti-cation based upon the user's behavior allows web sites and businesses to rationalize the risks they take when authorizing access to critical func-tionalities. In this paper, we propose a new model for implicit authen-tication of web users based on extraction of closed patterns. On a data set of web navigation connection logs of 3,000 users over a six-month period we follow the experimental protocol described in [1] to compute performance of our model.