Cao Cun-Zhang, He Chen-Guang, Bao Shu-Di, Li Ye
Key Lab for Health Informatics, Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, and Chinese Academy of Sciences.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:3563-7. doi: 10.1109/IEMBS.2011.6090594.
The security of Body Sensor Network (BSN) has become a vital concern, as the massive development of BSN applications in healthcare. A family of biometrics based security methods has been proposed in the last several years, where the bio-information derived from physiological signals is used as entity identifiers (EIs) for multiple security purposes, including node recognition and keying material protection. Among them, a method named as Physiological Signal based Key Agreement (PSKA) was proposed to use frequency-domain information of physiological signals together with Fuzzy Vault scheme to secure key distribution in BSN. In this study, the PSKA scheme was firstly analyzed and evaluated for its practical usage in terms of fuzzy performance, the result of which indicates that the scheme is not as good as claimed. An improved scheme with the deployment of Fuzzy Vault and error correcting coding was then proposed, followed by simulation analysis. The results indicate that the improved scheme is able to improve the performance of Fuzzy Vault and thus the success rate of authentication or key distribution between genuine nodes of a BSN.
随着人体传感器网络（BSN）在医疗保健领域的大规模发展，其安全性已成为至关重要的问题。在过去几年中，已经提出了一系列基于生物识别的安全方法，其中从生理信号中提取的生物信息被用作实体标识符（EI），用于多种安全目的，包括节点识别和密钥材料保护。其中，一种名为基于生理信号的密钥协商（PSKA）的方法被提出，该方法将生理信号的频域信息与模糊保险库方案相结合，以确保BSN中的密钥分发安全。在本研究中，首先对PSKA方案在模糊性能方面的实际应用进行了分析和评估，结果表明该方案并不像所声称的那样好。随后提出了一种部署模糊保险库和纠错编码的改进方案，并进行了仿真分析。结果表明，改进后的方案能够提高模糊保险库的性能，从而提高BSN中真实节点之间的认证成功率或密钥分发成功率。
