Free-text Keystroke Dynamics Authentication for Arabic Language

This paper introduces an approach for user authentication using free-text keystroke dynamics which incorporates text in Arabic language. The Arabic language has completely different characteristics to those of the English language, thus using typing patterns for Arabic input to authenticate users is an important contribution of this paper. The approach followed in this study involves the use of the keyboard’s key-layout. The method extracts timing features from specific key-pairs in the typed text. Decision trees were exploited to classify each of the users’ data. In parallel for comparison, Support Vector Machines (SVMs) were also used for classification in association with an Ant Colony Optimization (ACO) feature selection technique. The results obtained from this study are encouraging as low False Accept Rates (FAR) and False Reject Rates (FRR) were achieved in the experimentation phase. This signifies that satisfactory overall system performance was achieved by using the typing attributes in the proposed approach, while typing Arabic text.