Authentication of Lossy Data in Body-Sensor Networks for

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 smartphone or tablet, and then archived in the cloud by personal health record services. Authenticating the data these devices generate 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 design 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 i