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Monitor Node Selection Algorithm Based on Mutual Information in Wireless Mesh Networks

机译:基于无线网状网络中的相互信息的监视节点选择算法

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Intrusion Detection System (IDS) is considered as one of the most effective security mechanisms in wireless networks. However, nodes which are used to monitor the network abnormal behaviors will carry out amount of overhead and degrade network performance. In this paper, we propose a monitor node selection algorithm based on mutual information to solve the above issue. In the algorithm, we consider the importance of nodes and the influence between nodes. Moreover, we represent the importance of nodes' topological position with bridge connection coefficient, and takes degree of interaction between nodes into account. The mutual information value of node is determined and regarded as selection condition of monitor node. In order to allocate the range of monitor node efficiently, we introduce linear threshold model in the social network and consider similarity of node is as influence edge weight. Simulation results show that the proposed algorithm can effectively reduce system cost, ensure the accuracy of intrusion detection system and improve the network performance compared with the traditional node section schemes.
机译:入侵检测系统(IDS)被认为是无线网络中最有效的安全机制之一。但是,用于监控网络异常行为的节点将执行开销量和降低网络性能。在本文中,我们提出了一种基于相互信息的监视节点选择算法来解决上述问题。在算法中,我们考虑节点的重要性和节点之间的影响。此外,我们代表了节点的拓扑位置与桥接连接系数的重要性,并考虑了节点之间的相互作用。节点的互信息值被确定并视为监视节点的选择条件。为了有效地分配监视节点的范围,我们在社交网络中引入线性阈值模型,并考虑节点的相似性是影响边缘权重。仿真结果表明,该算法可以有效降低系统成本,确保入侵检测系统的准确性,与传统节点部分方案相比,改善网络性能。

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