Tele-healthcare could largely reduce national healthcare cost through remote self-managed patient monitoring. Cardiac Sensor Networks (CSNs) could be used to deploy such a system. Moreover, the integration of RFID into CSN could play an important role for elder healthcare because RFID could be used to monitor elders' medicine taking behaviors. On the other hand, the disclosure of RFID information during RFID tag-to-reader communications can cause the violation of patients' privacy. This research aims to achieve trustworthiness in a practical RFID-assisted CSN platform. This project will make the following three contributions: (1) Error-resistant ECG transmission: A trustworthy CSN should be able to overcome the impacts of radio interference and propagation distortions that can lead to frequent ECG transmission errors. This research will use the receiver-only local ECG processing to overcome ECG errors/loss. It will conduct a comparative study of two promising anti-interference methods, Kalman Filter and Tempo-spatial Regression. (2) Low-overhead RFID security: This research will design a lightweight RFID security scheme based on Linear Congruential Generator (LCG) and a mutual authentication scheme. The RFID security will be tested in our current CSN hardware platform. (3) CSN temporal accountability: In ECG sensor applications, all ECG anomaly detections depend on accountable time interval analysis between different ECG signal segments. This research will achieve CSN temporal accountability through the following two technical approaches: i) design a receiver-only clock uncertainty prediction model to avoid wireless communication overhead; and ii) design a history-aware, reputation based trust model to capture the evolutionary timing attacks.
