Physiological Signal Based Entity Authentication for Body Area Sensor Networks and Mobile Healthcare Systems

With the evolution of m-Health, an increasing number of biomedical sensors will be worn on or implanted in an individual in the future for the monitoring, diagnosis, and treatment of diseases. For the optimization of resources, it is therefore necessary to investigate how to interconnect these sensors in a wireless body area network, wherein security of private data transmission is always a major concern. This paper proposes a novel solution to tackle the problem of entity authentication in body area sensor network (BASN) for m-Health. Physiological signals detected by biomedical sensors have dual functions: (1) for a specific medical application, and (2) for sensors in the same BASN to recognize each other by biometrics. A feasibility study of proposed entity authentication scheme was carried out on 12 healthy individuals, each with 2 channels of photoplethysmogram (PPG) captured simultaneously at different parts of the body. The beat-to-beat heartbeat interval is used as a biometric characteristic to generate identity of the individual. The results of statistical analysis suggest that it is a possible biometric feature for the entity authentication of BASN.