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A novel biometrics method to secure wireless body area sensor networks for telemedicine and m-health

机译:一种保护远程医疗和移动医疗无线人体感应器网络安全的新型生物识别方法

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The development of the wireless body area sensor network (BASN) is imperative for modern telemedicine and m-health, but security remains a formidable challenge yet to be resolved. As nodes of BASN are expected to be interconnected on or in the human body, the body itself can form an inherently secure communication pathway that is unavailable to all other kinds of wireless networks. This article explores the use of this conduit in the security mechanism of BASN; that is, by a biometrics approach that uses an intrinsic characteristic of the human body as the authentication identity or the means of securing the distribution of a cipher key to secure inter-BASN communications. The method was tested on 99 subjects with 838 segments of simultaneous recordings of electrocardiogram and photoplethysmogram. By using the interpulse interval (IPI) as the biometric trait, the system achieved a minimum half total error rate of 2.58 percent when the IPIs measured from signals, which were sampled at 1000 Hz, were coded into 128-bit binary sequences. The study opens up a few key issues for future investigation, including compensation schemes for the asynchrony of different channels, coding schemes, and other suitable biometric traits.
机译:无线人体区域传感器网络(BASN)的发展对于现代远程医疗和移动医疗至关重要,但是安全性仍然是一个尚未解决的巨大挑战。由于期望BASN的节点在人体上或人体中互连,因此人体本身可以形成固有的安全通信路径,而该通信路径对于所有其他种类的无线网络均不可用。本文探讨了此管道在BASN的安全机制中的使用。也就是说,通过使用人体固有特征作为认证身份或确保密码密钥分配以确保BASN间通信安全的手段的生物识别方法。该方法在99位受试者上进行了838段心电图和光体积描记图的同时记录测试。通过将脉冲间隔(IPI)作为生物特征,将以1000 Hz采样的信号测得的IPI编码为128位二进制序列后,系统的最小半总错误率为2.58%。该研究为未来的研究提出了一些关键问题,包括针对不同通道的异步性的补偿方案,编码方案以及其他合适的生物特征。

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