Analysis of Template Update Strategies for Keystroke Dynamics Keystroke dynamics is a behavioral biometrics showing a degradation of performance when used over time. This is due to the fact that the user improves hisher way of typing while using the system, therefore the test samples may be different from the initial template computed at an earlier stage. One way to bypass this problem is to use template update mechanisms. We propose in this work, new semisupervised update mechanisms, inspired from known supervised ones. These schemes rely on the choice of two thresholds (an acceptance threshold and an update threshold) which are fixed manually depending on the performance of the system and the level of tolerance in possible inclusion of impostor data in the update template. We also propose a new evaluation scheme for update mechanisms, taking into account performance evolution over several timesessions. Our results show an improvement of 50% in the supervised scheme and of 45% in the semisupervised one with a configuration of the parameters chosen so that we do not accept many erroneous data.

Keyboard user verification: toward an accurate, efficient, and ecologically valid algorithm This paper proposes new measures of individual differences in typing behaviour which provide a means of accurately verifying the identity of the typist. A first study examined the efficacy of a multivariate measure of interkey latencies and a probabilistic discriminator statistic in conjunction with an individual filtering system which eliminates occasional disfluent keystrokes. The results indicate that, under optimum conditions but with a very small test sample, these measures lead to better typist verification than measures suggested earlier by Umphress and Williams and then Leggett and Williams. A second study validated the improved algorithm under more ecologically valid conditions and showed that when training and test sessions were separated by one week, typist verification using the new algorithm achieved combined falseacceptance and falserejection rates of 0.9% and 3.8% for test samples of 300 and 50 digraphs respectively.