为在面临大规模网络攻击或突发攻击时，提高入侵检测的实时性，提出基于云计算的舰船通信网络入侵检测方法。通过云计算的MapReduce编程模型，设计MapReduce并行化的遗传量子粒子群优化算法，在舰船通信网络数据内，提取网络入侵特征；利用MapReduce并行化熵聚类算法，确定径向基函数神经网络的基函数中心；确定基函数中心后，在MapReduce编程模型的Map函数内，输入网络入侵特征样本，训练神经网络，优化神经网络权值，通过Reduce函数输出训练结束指示，完成神经网络训练；在完成训练的MapReduce并行化径向基函数神经网络内，输入特征样本，输出舰船通信网络入侵检测结果。实验证明，该方法可有效提取舰船通信网络入侵特征；在不同网络攻击类型下，该方法均可精准完成舰船通信网络入侵检测。
To improve the real-time performance of intrusion detection in the face of large-scale network attacks or sudden attacks, a cloud computing based intrusion detection method for ship communication networks is studied. Using the MapReduce programming model of cloud computing, design a genetic quantum particle swarm optimization algorithm for MapReduce parallelization, and extract network intrusion features from ship communication network data; Using the MapReduce parallelized entropy clustering algorithm, determine the basis function center of the radial basis function neural network; After determining the center of the basis function, input network intrusion feature samples into the Map function of the MapReduce programming model, train the neural network, optimize the weights of the neural network, output training completion instructions through the Reduce function, and complete the neural network training; In the trained MapReduce parallelized radial basis function neural network, input feature samples and output intrusion detection results for ship communication networks. Experimental results have shown that this method can effectively extract intrusion features from ship communication networks; This method can accurately detect ship communication network intrusion under different types of network attacks.
2024,46(10): 170-173 收稿日期：2023-09-26
DOI：10.3404/j.issn.1672-7649.2024.10.030
分类号：TP311
作者简介：黄国峰(1975-),男,硕士,副教授,研究方向为计算机科学、网络安全及教育信息化
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