Performance Analysis of Free Text Keystroke Authentication Using XGBoost

Authentication based on keystroke dynamics is a form of behavioral biometric authentication that uses the user typing patterns and keyboard interaction as a discriminatory input. This type of authentication can be coupled with a fixed text password in a traditional login system to contribute to a multifactor authentication or provide continuous user authentication in a usable security system, where the typing patterns are continuously analysed to validate the user at run time. This paper investigates the effectiveness of free text keystroke for continuous authentication in real-world systems. Evaluation is performed using XGBoost multiclass classification, applied to an unbalanced free-text keystroke dataset. The introduction of additional activity-based features and removal of inaccuracies in the timing between keys allowed a reduction of the EER for the Clarkson II dataset from 14–24%, as achieved by previous studies, to 8% when employing the proposed method.