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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Continuous User Authentication Using Machine Learning on Touch Dynamics
verfasst von : Ştefania Budulan, Elena Burceanu, Traian Rebedea, Costin Chiru
Erschienen in: Neural Information Processing
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Abstract
In the context of constantly evolving carry-on technology and its increasing accessibility, namely smart-phones and tablets, a greater need for reliable authentication means comes into sight. The current study offers an alternative solution of uninterrupted testing towards verifying user legitimacy. A continuously collected dataset of 41 users’ touch-screen inputs provides a good starting point into modeling each user’s behavior and later differentiate among users. We introduce a system capable of processing features based on raw data extracted from user-screen interactions and attempting to assign each gesture to its originator. Achieving an accuracy of over 83 %, we prove that this type of authentication system is feasible and that it can be further integrated as a continuous way of disclosing intruders within given mobile applications.