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A Distributed Trust Evaluation Model and Its Application Scenarios for Medical Sensor Networks

机译:医疗传感器网络的分布式信任评估模型及其应用场景

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摘要

The development of medical sensor networks (MSNs) is imperative for e-healthcare, but security remains a formidable challenge yet to be resolved. Traditional cryptographic mechanisms do not suffice given the unique characteristics of MSNs, and the fact that MSNs are susceptible to a variety of node misbehaviors. In such situations, the security and performance of MSNs depend on the cooperative and trust nature of the distributed nodes, and it is important for each node to evaluate the trustworthiness of other nodes. In this paper, we identify the unique features of MSNs and introduce relevant node behaviors, such as transmission rate and leaving time, into trust evaluation to detect malicious nodes. We then propose an application-independent and distributed trust evaluation model for MSNs. The trust management is carried out through the use of simple cryptographic techniques. Simulation results demonstrate that the proposed model can be used to effectively identify malicious behaviors and thereby exclude malicious nodes. This paper also reports the experimental results of the Collection Tree Protocol with the addition of our proposed model in a network of TelosB motes, which show that the network performance can be significantly improved in practice. Further, some suggestions are given on how to employ such a trust evaluation model in some application scenarios.
机译:医疗传感器网络(MSN)的发展对于电子医疗至关重要,但是安全性仍然是一个尚未解决的巨大挑战。考虑到MSN的独特特征以及MSN易受多种节点错误行为影响的事实,传统的加密机制不足以满足要求。在这种情况下,MSN的安全性和性能取决于分布式节点的协作和信任性质,并且每个节点评估其他节点的信任度很重要。在本文中,我们确定了MSN的独特功能,并将相关的节点行为(如传输速率和离开时间)引入信任评估以检测恶意节点。然后,我们提出了MSN的独立于应用程序的分布式信任评估模型。信任管理是通过使用简单的密码技术来执行的。仿真结果表明,该模型可以有效识别恶意行为,从而排除恶意节点。本文还报告了收集树协议的实验结果,并在TelosB节点网络中添加了我们提出的模型,这表明在实践中可以显着提高网络性能。此外,对于在某些应用场景中如何采用这种信任评估模型,提出了一些建议。

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