Authentication of lossy data in body-sensor networks for healthcare monitoring

Growing pressures on healthcare costs are spurring development of lightweight bodyworn sensors for real-time and continuous physiological monitoring. Data from these sensors is streamed wirelessly to a handheld device such as a mobile phone, and then archived over the Internet at a central database. Authenticating the data is vital to ensure proper diagnosis, traceability, and validation of claims. Digital signatures at the packet-level are too resource-intensive for bodyworn devices, while block-level signatures are not robust to loss. In this paper we propose, analyse, and validate a practical, lightweight robust authentication scheme suitable for health-monitoring. We make three specific contributions: (a) We develop an authentication scheme that is both low-cost (using a Merkle hash tree to amortise digital signature costs), and loss-resilient (using network coding to recover strategic nodes within the tree). (b) We develop a framework for optimising placement of network coding within the tree to maximise data verifiability for a given overhead and loss environment. (c) We validate our scheme using experimental traces of typical operating conditions to show that it achieves high success (over 99% of the medical data can be authenticated) at very low overheads (as low as 5% extra transmissions) and at very low cost (the bodyworn device has to perform a digital signature operation no more than once per hour). We believe our novel authentication scheme can be a key ingredient in the integration of wearable medical monitoring devices into current healthcare systems.