An unsupervised approach for gait-based authentication

• Published in: Proceedings (International Conference on Wearable and Implantable Body Sensor Networks : Print) pp. 1 - 6
• Main Authors: Cola, Guglielmo, Avvenuti, Marco, Vecchio, Alessio, Guang-Zhong Yang, Lo, Benny
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2015
• Subjects: Acceleration; Anomaly Detection; Authentication; Detection algorithms; Feature extraction; Gait Analysis; Gait-Based Authentication; Legged locomotion; Monitoring; Training; Wearable sensors

Similar to fingerprint and iris pattern, everyone's gait is unique, and gait has been proposed as a biometric feature for security applications. This paper presents a lightweight accelerometer-based technique for user authentication on smart wearable devices. Designed as an unsupervised classif...