Multi-sensor context-awareness in mobile devices and smart artifacts
Mobile Networks and Applications
EigenGait: Motion-Based Recognition of People Using Image Self-Similarity
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Guide to Biometrics
Communications of the ACM - Multimodal interfaces that flex, adapt, and persist
A tutorial on text-independent speaker verification
EURASIP Journal on Applied Signal Processing
Gesture interaction for small handheld devices to support multimedia applications
Journal of Mobile Multimedia
PDA Security: PDA security concerns
Network Security
Automatic gait recognition based on statistical shape analysis
IEEE Transactions on Image Processing
Biometrics Driven Smart Environments: Abstract Framework and Evaluation
UIC '08 Proceedings of the 5th international conference on Ubiquitous Intelligence and Computing
Review: Ambient intelligence: Technologies, applications, and opportunities
Pervasive and Mobile Computing
Quantifying Gait Similarity: User Authentication and Real-World Challenge
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Gait recognition using wearable motion recording sensors
EURASIP Journal on Advances in Signal Processing - Special issue on recent advances in biometric systems: a signal processing perspective
Speaker model updating by the conversational sounds in speaker verification
Proceedings of the 12th International Conference on Information Integration and Web-based Applications & Services
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The need for authenticating users of ubiquitous mobile devices is becoming ever more critical with the increasing value of information stored in the devices and of services accessed via them. Passwords and conventional biometrics such as fingerprint recognition offer fairly reliable solutions to this problem, but these methods require explicit user authentication and are used mainly when a mobile device is being switched on. Furthermore, conventional biometrics are sometimes perceived as privacy threats. This paper presents an unobtrusive method of user authentication for mobile devices in the form of recognition of the walking style (gait) and voice of the user while carrying and using the device. While speaker recognition in noisy conditions performs poorly, combined speaker and accelerometer-based gait recognition performs significantly better. In tentative tests with 31 users the Equal Error Rate varied between 2% and 12% depending on noise conditions, typically less than half of the Equal Error Rates of individual modalities.