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Hierarchical trust-based black-hole detection in WSN-based smart grid monitoring

机译:基于WSN的智能电网监控中的基于分层信任的黑洞检测

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Wireless Sensor Networks (WSNs) have been widely adopted to monitor various ambient conditions including critical infrastructures. Since power grid is considered as a critical infrastructure, and the smart grid has appeared as a viable technology to introduce more reliability, efficiency, controllability, and safety to the traditional power grid, WSNs have been envisioned as potential tools to monitor the smart grid. The motivation behind smart grid monitoring is to improve its emergency preparedness and resilience. Despite their effectiveness in monitoring critical infrastructures, WSNs also introduce various security vulnerabilities due to their open nature and unreliable wireless links. In this paper, we focus on the, Black-Hole (B-H) attack. To cope with this, we propose a hierarchical trust-based WSN monitoring model for the smart grid equipment in order to detect the B-H attacks. Malicious nodes have been detected by testing the trade-off between trust and dropped packet ratios for each Cluster Head (CH). We select different thresholds for the Packets Dropped Ratio (PDR) in order to test the network behaviour with them. We set four different thresholds (20%, 30%, 40%, and 50%). Threshold of 50% has been shown to reach the system stability in early periods with the least number of re-clustering operations.
机译:无线传感器网络(WSNS)已被广泛采用以监控各种环境条件,包括关键基础架构。由于电网被认为是一个关键的基础设施,并且智能电网出现为可行的技术,以引入传统电网的更多可靠性,效率,可控性和安全性,因此已设想监控智能电网的潜在工具。智能电网监测背后的动机是提高其紧急准备和恢复力。尽管他们在监控关键基础设施方面有效性,但WSN也引入了由于其开放性和不可靠的无线链路而导致的各种安全漏洞。在本文中,我们专注于黑洞(B-H)攻击。为了应对这一点,我们提出了一种用于智能电网设备的基于分层信任的WSN监控模型,以检测B-H攻击。通过测试每个群集头(CH)的信任和丢弃的数据包比之间的权衡来检测恶意节点。我们为数据包丢弃比率(PDR)选择不同的阈值,以便与它们测试网络行为。我们设置了四个不同的阈值(20 %,30 %,40 %和50 %)。已经显示50 %的阈值,以便在具有最少数量的重新聚类操作中达到系统稳定性。

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