ECG-Based User Authentication and Identification Method on VANETs

Industry and academia continuously look for improvements in data security and privacy due to the increasing amount of pervasive applications launched every day. This paper investigates the use of electrocardiogram (ECG) as an authentication factor in VANETs and shared car context. Other authentication approaches exist, but many of them do not apply continuous authentication, resulting in scenarios where illegitimate drivers can use the vehicle as it is unlocked and on. ECG has historically been employed for healthcare monitoring and, only recently, as a biometric based on the QRS graphical deflections. We exploit the ECG biometric aspect and we employ a fiducial point detection algorithm based on Hill Climbing to detect the QRS complex. Our approach is feasible given the small time window required for data collection and the simple QRS detection process, which can be implemented in any device, different from other complex proposals.