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Proposing an Intrusion Detection System in Energy-Aware Wireless Sensor Networks Using Neural Networks and Fuzzy Logic-Based Genetic Algorithm

机译:使用神经网络和模糊逻辑遗传算法在能量感知无线传感器网络中提出入侵检测系统

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摘要

This study proposes an Intrusion Detection System (IDS) in Wireless Sensor Networks (WSNs) which is aware of energy at the sleeping and awake times of the network. Different systems are used for detecting intrusion which are capable of training, classification, clustering, testing and evaluation through the help of various algorithms and combinatory modes. In this study, a combination of probabilistic neural networks and fuzzy-logic based genetic algorithm was used. The proposed method was simulated using KDD99 dataset. The statistical analysis of the implementation and simulation results indicated that the proposed method has higher efficiency than the earlier methods.
机译:本研究提出了一种无线传感器网络(WSN)中的入侵检测系统(IDS),其意识到网络的睡眠和唤醒时间的能量。 不同的系统用于通过各种算法和组合模式检测能够培训,分类,聚类,测试和评估的入侵。 在该研究中,使用了概率神经网络和模糊基于基于模糊逻辑的遗传算法的组合。 使用KDD99数据集进行模拟所提出的方法。 实施和仿真结果的统计分析表明,该方法的效率高于前面的方法。

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