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Keystroke dynamics Based Technique to Enhance the Security in Smart Devices

Nowadays, smart devices have become a part of our lives, hold our data, and are used for sensitive transactions like internet banking, mobile banking, etc. Therefore, it is crucial to secure the data in these smart devices from theft or misplacement. The majority of the devices are secured with password/PINbased user authentication methods, which are already proved a less secure or easily guessable user authentication method. An alternative technique for securing smart devices is keystroke dynamics. Keystroke dynamics (KSD) is behavioral biometrics, which uses a natural typing pattern unique in every individual and difficult to fake or replicates that pattern. This paper proposes a user authentication model based on KSD as an additional security method for increasing the smart devices’ security level. In order to analyze the proposed model, an android-based application has been implemented for collecting data from fake and genuine users. Six machine learning algorithms have been tested on the collected data set to study their suitability for use in the keystroke dynamics-based authentication model.