Monitoring patients via a secure and mobile healthcare system
IEEE Wireless Communications
A survey on wireless body area networks
Wireless Networks
Body sensor network mobile solutions for biofeedback monitoring
Mobile Networks and Applications - Special issue on Wireless and Personal Communications
Body area network security: robust key establishment using human body channel
HealthSec'12 Proceedings of the 3rd USENIX conference on Health Security and Privacy
Biometric verification of a subject through eye movements
Computers in Biology and Medicine
Balancing security and utility in medical devices?
Proceedings of the 50th Annual Design Automation Conference
Heart-to-heart (H2H): authentication for implanted medical devices
Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security
BDK: secure and efficient biometric based deterministic key agreement in wireless body area networks
BodyNets '13 Proceedings of the 8th International Conference on Body Area Networks
Adaptive entity-identifier generation for IMD emergency access
Proceedings of the First Workshop on Cryptography and Security in Computing Systems
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Security of the emerging body sensor network (BSN) in telemedicine applications is a crucial problem because personal medical information must be protected against flaws and misdeeds. The solution is, however, nontrivial because lightweight mechanisms have to be deployed to meet the stringent resource constraints of these networks. It has been suggested that the inherent ability of human body to transfer information is a unique and resource-saving method to secure wireless communications within a BSN. For example, physiological characteristics can be captured by individual sensors of a BSN to generate entity identifiers (EIs) for identifying nodes and even securing keying materials, i.e., by a biometric approach. This study demonstrates the performance analysis of such a biometric trait, i.e., the interpulse intervals (IPIs) of heartbeats that were calculated from electrocardiogram and photoplethysmogram of 99 subjects. Based on the characteristics of IPIs, a lightweight generation scheme of EIs is proposed. Individual randomness and group similarity of the generated EIs are then evaluated. False acceptance rate and false rejection rate are also calculated to measure the effectiveness of the proposed identification system. The results suggest that the readily available IPI information can be a good source for generating EIs among BSN nodes.