Hong Tian, Bao Shu-Di, Zhang Yuan-Ting, Li Ye, Yang Ping
Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, and Key Lab for Health Informatics, Chinese Academy of Science.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:1519-22. doi: 10.1109/IEMBS.2011.6090366.
Securing body sensor network (BSN) in an efficient manner is very important for preserving the privacy of medical data. Protecting data confidentiality, integrity and to authenticate the communicating nodes are basic requirements to secure BSN. The existing method to generate entity identifier (EI) from inter-pulse intervals (IPIs) of heartbeats has its advantages in authenticating and identifying nodes, which however was found in this study that such generated EIs are not so resistant to attacks because of potential error patterns. This paper presents an improved scheme of IPI-based EI generation to eliminate the error patterns. The performance of randomness and node identification, i.e. false acceptance rate and false rejection rate, is experimentally evaluated. The results indicate that compared with the existing one, the new scheme is effective to eliminate the error patterns and thus more tolerant to attacks, while there is no compromise on the randomness level and identification performance.
以高效方式保护人体传感器网络（BSN）对于保护医学数据的隐私非常重要。保护数据机密性、完整性以及对通信节点进行认证是确保BSN安全的基本要求。现有的从心跳的脉冲间期（IPI）生成实体标识符（EI）的方法在认证和识别节点方面具有优势，然而本研究发现，由于潜在的错误模式，此类生成的EI对攻击的抵抗力不强。本文提出了一种改进的基于IPI的EI生成方案以消除错误模式。通过实验评估了随机性和节点识别的性能，即错误接受率和错误拒绝率。结果表明，与现有方案相比，新方案能有效消除错误模式，因此对攻击的耐受性更强，同时在随机性水平和识别性能上没有妥协。
