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An improved scheme of IPI-based entity identifier generation for securing body sensor networks

机译:基于IPI的实体标识符生成的改进方案,用于保护身体传感器网络的生成

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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.
机译:以有效的方式保护身体传感器网络(BSN)对于保留医疗数据的隐私非常重要。保护数据机密性,完整性和验证通信节点是安全BSN的基本要求。从心跳的脉冲间隔(IPI)生成实体标识符(EI)的现有方法在验证和识别节点方面具有其优点,然而在该研究中发现,这种产生的EIS由于潜在的误差而言,这种生成的EIS不会抵抗攻击模式。本文介绍了基于IPI的EI生成的改进方案,以消除误差模式。实验评估随机性和节点识别的性能,即假验收率和假拒绝率。结果表明,与现有的结果相比,新方案有效地消除误差模式,从而更容忍攻击,而无需对随机性水平和识别性能没有妥协。

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