舰船通信网络混合入侵数据自适应识别技术

Adaptive identification technology of mixed intrusion data in ship communication network

针对目前舰船通信网络混合入侵数据数量大、识别精准度低这一问题进行分析,提出了一种新的识别技术。该技术的工作过程如下:首先设定混合入侵数据阈值,比较聚类中心和混合入侵数据所属区域的偏离程度,然后在所有的通信网络数据中识别出混合入侵数据,建立二维网络,最后找出相似度较高的混合入侵数据的差异,完成精准识别。对比实验结果表明,相较于传统方法,所研究的技术更加重视加权处理和过滤处理,使混合入侵数据能够拥有最大的识别结构,识别起来更加容易,在识别混合入侵数据时有很强的能力,识别结果精准度高,有效提高了通信网络运行过程的安全性,具有很大的发展潜力。

Aiming at the problem of large number of mixed intrusion data and low accuracy of identification in ship communication network, a new identification technology is proposed. The work process of this technology is as follows:Firstly, the threshold of mixed intrusion data is set, and the deviation degree between the clustering center and the region where the mixed intrusion data belong is compared. Then, the mixed intrusion data is identified in all communication network data, and a two-dimensional network is established. Finally, the difference of the mixed intrusion data with high similarity is found. Accurate identification. The experimental results show that compared with the traditional methods, the proposed techniques pay more attention to the weighted processing and filtering processing, so that the mixed intrusion data can have the largest identification structure, and it is easier to identify. The hybrid intrusion data has a strong ability to identify the Mixed Intrusion data, and the recognition results have high accuracy, which effectively improves the communication network. The safety of the running process has great potential for development.