Darabseh, AlaaNamin, Akbar SiamiBrömme, ArslanBusch, ChristophRathgeb, ChristianUhl, Andreas2017-06-302017-06-302015978-3-88579-639-8The aim of this research is to advance the user active authentication using keystroke dynamics. Through this research, we assess the performance and influence of various keystroke features on keystroke dynamics authentication systems. In particular, we investigate the performance of keystroke features on a subset of most frequently used English words. The performance of four features such as i) key duration, ii) flight time latency, iii) digraph time latency, and iv) word total time duration are analyzed. Experiments are performed to measure the performance of each feature individually as well as the results from the different subsets of these features. Four machine learning techniques are employed for assessing keystroke authentications. TheenText/Conference Paper1617-5468