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An Enhanced Sociopsychological-based Trust Model for Boosting Security in Wireless Sensors Networks

机译:基于增强的社会心理学的信任模型,用于在无线传感器网络中提升安全性

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Wireless sensor network (WSN) is growing exponentially, as well as WSN attacks. Trust between nodes in WSNs is emerging as a crucial factor in WSN security, since nodes cooperation is vital besides their capability of sensing, processing and communicating data. Research on security in WSNs has explored cryptography mechanisms, intrusion detection systems. Using these traditional techniques to eliminate insider attacks is possible but is inefficient in WSNs due to computational limitations. In this paper, we propose an enhanced sociopsychological-based trust model that utilizes fuzzy logic for realistically relate the Ability, Benevolence and Integrity components to get better and smooth trust rating, which in turn enhances the WSN stability. Preliminary results of our model show good improvement in trust rating computation over the original model.
机译:无线传感器网络(WSN)呈指数增长,以及WSN攻击。 WSN中的节点之间的信任作为WSN安全性的关键因素,因为节点合作除了它们对传感,处理和通信数据的能力之外。 WSN中的安全性研究已经探索了加密机制,入侵检测系统。使用这些传统技术来消除内幕攻击是可能的,但由于计算限制,WSN中的效率低。在本文中,我们提出了一种增强的社会心神经的信任模型,利用模糊逻辑来实现更好地涉及的能力,仁慈和完整性分量,以获得更好和平稳的信任评级,这又提高了WSN稳定性。我们模型的初步结果显示了原始模型上的信任评级计算良好的改进。

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