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首页> 外文期刊>Ad-hoc & sensor wireless networks >Artificial Neural Network Based Detection of Energy Exhaustion Attacks in Wireless Sensor Networks Capable of Energy Harvesting
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Artificial Neural Network Based Detection of Energy Exhaustion Attacks in Wireless Sensor Networks Capable of Energy Harvesting

机译:基于人工神经网络的能量收集无线传感器网络能量耗尽攻击检测

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摘要

Energy consumption is the important factor when designing any mechanism for wireless sensor network (WSN). Research community is trying to enable energy harvesting mechanisms to provide long term energy source to WSN. However, energy consumption is generally greater than energy harvesting in WSN. Furthermore, if nodes are under any kind of energy exhaustion security attack, then energy harvesting mechanism cannot extend the lifetime of the WSN. In this paper, we propose a detection mechanism of energy exhaustion attacks that uses an artificial neural network (ANN). It has been developed for cluster-based WSN and takes into account the energy harvesting system. Simulation results show that our mechanism can detect and prevent such kind of attacks, even having lower percentage of false positives than other systems, and thus enlarge the wireless sensor node lifetime.
机译:在设计用于无线传感器网络(WSN)的任何机制时,能耗是重要的因素。研究团体正在尝试使能量收集机制能够为WSN提供长期能源。但是,能量消耗通常大于WSN中的能量收集。此外,如果节点受到任何形式的能量耗尽安全攻击,则能量收集机制将无法延长WSN的寿命。在本文中,我们提出了一种使用人工神经网络(ANN)的能量耗尽攻击的检测机制。它已针对基于集群的WSN开发,并考虑了能量收集系统。仿真结果表明,我们的机制可以检测和阻止此类攻击,即使误报率低于其他系统,也可以延长无线传感器节点的使用寿命。

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