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), ISSN 0749-0208.
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.