An ECG-Based Authentication Scheme for Body Area Networks

Biometrics is the field of identifying subjects based on physiological and behavioral characteristics. Over the past few years, the electrocardiogram signal has become a hot topic in human identity recognition, mainly due to its robustness to attacks, universality and liveness detection. This paper makes use of these properties to generate ECG-based hash codes for inter-sensor authentication in body area networks. Mutual authentication prevents unauthorized access to sensors and actuators. The solution is lightweight and does not require a high computing power, making it perfect for small, wearable or body implanted sensors. Moreover, since only the hash code is transmitted, no sensitive-health related data is exposed. Finally, since the ECG signals used for hash generation are collected from different parts of the same subject, the mechanism is not vulnerable to errors due to physiological and psychological stress.