Research on intrusion detection method of marine meteorological sensor network based on anomalous behaviors

Abstract

To deal with the abnormal data flow attacks faced by the marine meteorological sensor network (MMSN), analyze the security mechanism, and aim at the complex and huge network structure and the extremely imbalanced data flow in the nodes, the intrusion detection method of marine meteorological sensor network based on anomalous behaviors was studied, and intrusion detection system (IDS) was built. The imbalance of dataset was considered emphatically, and the effective data generation was realized by using depth generation network CVAE-GAN to learn the distribution of minority classes in the dataset. OPTICS-based denoising algorithm was used to remove the noise points in majority classes and clarify the category boundaries. From the data perspective, the imbalance rate of dataset was reduced, the influence of imbalanced dataset on IDS was reduced, and the ability of classifier to identify minority classes of abnormal traffic was improved. The simulation results show that the proposed system can effectively identify all kinds of abnormal traffic, especially minority classes of them, and the imbalanced dataset processing method can significantly improve the detection ability of the classifier. © 2023 Editorial Board of Journal on Communications. All rights reserved.