Communications of the ACM
User authentication through keystroke dynamics
ACM Transactions on Information and System Security (TISSEC)
Keystroke analysis of free text
ACM Transactions on Information and System Security (TISSEC)
Acoustic Ear Recognition for Person Identification
AUTOID '05 Proceedings of the Fourth IEEE Workshop on Automatic Identification Advanced Technologies
The design and analysis of graphical passwords
SSYM'99 Proceedings of the 8th conference on USENIX Security Symposium - Volume 8
2D and 3D face recognition: A survey
Pattern Recognition Letters
On predictive models and user-drawn graphical passwords
ACM Transactions on Information and System Security (TISSEC)
A multi-matcher for ear authentication
Pattern Recognition Letters
Java-ML: A Machine Learning Library
The Journal of Machine Learning Research
User evaluation of lightweight user authentication with a single tri-axis accelerometer
Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services
Smudge attacks on smartphone touch screens
WOOT'10 Proceedings of the 4th USENIX conference on Offensive technologies
Tap-Wave-Rub: lightweight malware prevention for smartphones using intuitive human gestures
Proceedings of the sixth ACM conference on Security and privacy in wireless and mobile networks
Proceedings of the 19th annual international conference on Mobile computing & networking
Electronic Commerce Research
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In this paper we propose a new biometric measure to authenticate the user of a smartphone: the movement the user performs when answering (or placing) a phone call. The biometric measure leverages features that are becoming commodities in new smartphones, i.e. accelerometer and orientation sensors. We argue that this new biometric measure has a unique feature. That is, it allows a transparent authentication (not requiring an additional specific interaction for this) to check that the user that is answering (or placing) a phone call is the one authorized to do that. At the same time, this biometric measure can also be used as a non transparent authentication method, e.g. the user may need to move the phone as if answering a call, in order to unlock the phone to get access to SMSs or emails. As a consequence of being a biometric measure, an adversary that spies on the movement (e.g. captures it with a camera) and tries to replicate it, will not be granted access to the phone. We prototyped our solution and conducted several experiments to assess its feasibility. Results show that the method is effective, and the performance is comparable to that of other transparent authentication methods, like face or voice recognition.