Collaborative Intrusion Detection Method for Marine Distributed Network
Collaborative Intrusion Detection Method for Marine Distributed Network
复制标题
海洋分布式网络协同入侵检测方法
DOI：
10.2112/si83-010.1
复制
发表时间：
2019
影响因子：
--
通讯作者：
X. Li
中科院分区：
文献类型：
--
作者：
X. Li
摘要Li，X.，2018.一种海洋分布式网络协同入侵检测方法。In：Liu，Z.L.和Mi，C.（编辑），可持续港口和海洋工程进展。海洋研究杂志，第83号特刊，页。57-61.椰子溪（佛罗里达），ISSN 0749 -0208。针对目前海洋分布式网络广泛采用的基于支持向量机的入侵检测方法存在时延长，无法及时提供检测信息的问题，提出一种基于聚类的海洋分布式网络协同入侵检测方法。该方法首先利用相关分析方法对海洋分布式网络数据进行挖掘，并通过基于相对决策熵的决策树算法和差异度算法对海洋分布式网络数据进行聚类。在此基础上，根据海洋分布式网络入侵的属性特点，构建入侵检测模型，通过均值和方差完成海洋分布式网络的海洋协同入侵检测。实验结果表明，该方法不仅占用内存空间少，而且检测率在92%以上，提高了入侵检测的准确率。
ABSTRACT Li, X., 2018. Collaborative intrusion detection method for marine distributed network. In: Liu, Z.L. and Mi, C. (eds.), Advances in Sustainable Port and Ocean Engineering. Journal of Coastal Research, Special Issue No. 83, pp. 57–61. Coconut Creek (Florida), ISSN0749-0208. Aiming at the problem that the intrusion detection method based on support vector machine widely used by current marine distributed network has a long delay, which is unable to provide detection information in time, this paper proposes a collaborative intrusion detection method of marine distributed network based on clustering. Firstly, this method uses correlation analysis method for mining data in marine distributed network, and clusters the marine distributed network data through the decision tree algorithm based on the relative decision entropy and the difference degree algorithm. On this basis, according to the attribute characteristics of marine distributed network intrusion, we build the intrusion detection model, and complete the marine collaborative intrusion detection of marine distributed network through the mean and variance. Experimental result shows that the proposed method not only occupies less memory space, but also its detection rate is above 92%, which improves the accuracy of intrusion detection.