Abstract
The use of keystroke dynamics for user authentication has evolved over the years and has found its application in mobile phones. But the primary challenge with mobile phones is that they can be used in any position. Thus, it becomes critical to analyze the use of keystroke dynamics using the data collected in various typing positions. This research proposed a three-step authentication model that could be used to authenticate a user who is using the mobile in sitting, walking, and relaxing position. Furthermore, the mobile orientation (portrait and landscape) was considered while taking input from the user. Apart from using traditional keystroke features, accelerometer data were also combined for classification using Random Forest(RF) and K-Nearest Neighbour(KNN) classifiers. The three-step authentication method was able to authenticate a user with an EER of 2.9% for the relaxing landscape position. Finally, the model was optimized using Particle Swarm Optimization (PSO) to reduce the feature set and make the model more practical for mobile phones. Optimization helped to reduce the number of features from 55 to 17 and improved the EER to 2.2%. The research validated that relaxing and walking positions are the best positions to authenticate a user using keystroke dynamics.
Highlights
Mobile phones have become part of our daily life
The results show that the Random Forest classifier outperformed KNN for all situations
This study presented the results of a study aimed at using keystroke dynamics for authenticating a mobile user in different positions
Summary
Mobile phones have become part of our daily life. We start our day by looking at our social media/email notifications on the mobile phone. Saini et al.: Three-Step Authentication Model for Mobile Phone User Using Keystroke Dynamics. Some of the recent studies [16], [17] considered taking the input from the user in different positions like sitting, walking, and standing. Based on the literature review done to our best efforts no study so far has analyzed the user typing behavior in the above mentioned three different positions, i.e., sitting, walking, and relaxing. This study proposes a novel three-step model of user authentication in three environments, i.e., sitting, walking, and relaxing, and holding the phone in both orientations, i.e., portrait and landscape. The main contribution of this paper are: Development of a three-step model for user authentication applicable in three typing positions - sitting, walking and relaxing.
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