网络入侵中的可用节点优化识别仿真研究

发布时间：2019-05-23 08:13

【摘要】：网络入侵中的可用节点进行准确识别,可以在发生网络入侵时,寻找可用节点保证网络正常运作。在可用节点识别过程中,应对网络节点安全性进行准确判断,精确的计算出节点可用性,但是传统方法依据拓扑势理论,构建网络入侵中的可用节点识别模型,但不能对网络节点可用性进行准确计算,导致识别出的节点中仍还有大量的无效节点,降低了节点识别的准确性。提出一种基于互信息的网络入侵中的可用节点优化识别模型。上述模型先将入侵网络的每条边都定义为一个信息流,获取每条边上相同节点的概率分布,对网络初始条边上节点的机密性、完整性和可用性进行无量纲化处理,比较网络机密性、完整性和可用性在网络入侵状态下的权重,组建网络节点安全性的判定矩阵,计算出网络入侵中的节点可用性重要度识别指标,利用计算的结果组建网络入侵中的可用节点识别模型。仿真实验证明,所提模型可以全面有效地完成对网络入侵中的可用节点识别,提高网络的连通性。
[Abstract]:The available nodes in the network intrusion can be identified accurately, and the available nodes can be found to ensure the normal operation of the network in the event of network intrusion. In the process of available node identification, the security of network nodes should be judged accurately and the availability of nodes should be calculated accurately. However, according to the topological potential theory, the available node identification model in network intrusion is constructed. However, the availability of network nodes can not be calculated accurately, resulting in a large number of invalid nodes in the identified nodes, which reduces the accuracy of node identification. In this paper, an optimal identification model of available nodes in network intrusion based on mutual information is proposed. In the above model, each edge of the intrusion network is defined as an information flow, the probability distribution of the same node on each side is obtained, and the confidentiality, integrity and availability of the nodes on the initial edge of the network are dimensionless. The weights of network confidentiality, integrity and availability in the state of network intrusion are compared, the decision matrix of network node security is established, and the identification index of node availability importance in network intrusion is calculated. The available node identification model in network intrusion is constructed by using the calculated results. The simulation results show that the proposed model can fully and effectively identify the available nodes in network intrusion and improve the connectivity of the network.
【作者单位】：南开大学滨海学院;
【分类号】：TP393.08

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