Collaborative Research: CT-ISG: Error-resistant, Accountable, RFID-assisted Wireless Sensor Networks for Elder Cardiac Tele-Healthcare

远程保健可以通过远程自我管理病人监测，在很大程度上降低国家保健费用。心脏传感器网络（csn）可以用来部署这样一个系统。此外，将RFID集成到CSN中可以发挥重要作用，因为RFID可以用于监测老年人的服药行为。另一方面，RFID标签与读写器通信过程中RFID信息的泄露会造成患者隐私的侵犯。本研究旨在实现rfid辅助CSN平台的可信赖性。本项目将做出以下三个贡献：(1)抗错误心电传输：一个值得信赖的CSN应该能够克服无线电干扰和传播扭曲的影响，这些干扰和传播扭曲会导致频繁的心电传输错误。本研究将使用仅接收器的局部心电处理来克服心电错误/丢失。本文将对卡尔曼滤波和时空回归两种很有前途的抗干扰方法进行比较研究。(2)低开销RFID安全：本研究将设计一个基于线性同余发生器（Linear Congruential Generator， LCG）和相互认证方案的轻量级RFID安全方案。RFID的安全性将在我们现有的CSN硬件平台上进行测试。(3) CSN时间责任：在心电传感器应用中，所有的心电异常检测都依赖于不同心电信号段之间的时间间隔责任分析。本研究将通过以下两种技术途径实现CSN的时间责任：1)设计一个仅接收方时钟不确定性预测模型，以避免无线通信开销；ii)设计一个历史感知的、基于信誉的信任模型来捕获进化定时攻击。

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.