免疫理论的船舶网络入侵检测方法
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摘要
为了提高船舶网络系统的安全性,针对当前船舶网络入侵检测方法误检率高的缺陷,设计了免疫理论的船舶网络入侵检测方法。首先对船舶网络入侵检测的原理进行分析,提取船舶网络入侵检测的原始数据,然后根据免疫理论对船舶网络入侵检测数据进行处理,提取船舶网络入侵检测特征,然后机器学习算法对船舶网络入侵检测行为进行建模,最后编程实现了船舶网络入侵检测算法,并与其他船舶网络入侵检测方法进行对比实验。结果表明,免疫理论可以提取更加有效的船舶网络入侵检测特征,提升了船舶网络入侵检测效率,而且船舶网络入侵检测正确率更高,减少了船舶网络入侵的误检率,是一种可行、有效的船舶网络入侵检测方法。
In order to improve the security of ship network system, aiming at the high false detection rate of current ship network intrusion detection methods, a ship network intrusion detection method based on immune theory is designed.Firstly, the principle of ship network intrusion detection is analyzed, and the original data of ship network intrusion detection is extracted. Then, the data of ship network intrusion detection is processed according to immune theory, and the intrusion detection characteristics of ship network are extracted. Then, the intrusion detection behavior of ship network is modeled by machine learning algorithm. Finally, the ship network intrusion detection algorithm is programmed and implemented. Compared with other methods of ship network intrusion detection, the results show that immune theory can extract more effective features of ship network intrusion detection, improve the efficiency of ship network intrusion detection, and the correct rate of ship network intrusion detection is higher, which reduces the false detection rate of ship network intrusion. It is a feasible and effective method of ship network intrusion detection.
In order to improve the security of ship network system, aiming at the high false detection rate of current ship network intrusion detection methods, a ship network intrusion detection method based on immune theory is designed.Firstly, the principle of ship network intrusion detection is analyzed, and the original data of ship network intrusion detection is extracted. Then, the data of ship network intrusion detection is processed according to immune theory, and the intrusion detection characteristics of ship network are extracted. Then, the intrusion detection behavior of ship network is modeled by machine learning algorithm. Finally, the ship network intrusion detection algorithm is programmed and implemented. Compared with other methods of ship network intrusion detection, the results show that immune theory can extract more effective features of ship network intrusion detection, improve the efficiency of ship network intrusion detection, and the correct rate of ship network intrusion detection is higher, which reduces the false detection rate of ship network intrusion. It is a feasible and effective method of ship network intrusion detection.
引文
[1]陈颜,贾如春.基于四层过滤的船舶通信网络入侵检测模型研究[J].舰船科学技术,2018,40(9A):157-159.
[2]吴雪毅,李君芳.船舶网络中的高精度入侵检测方法设计[J].舰船科学技术,2018,40(5A):157-159.
[3]黄超.云计算下船舶网络入侵高精度检测方法研究[J].舰船科学技术,2018,40(6A):130-132.
[4]陈志忠.船舶监控网络入侵检测系统设计[J].舰船科学技术,2018,40(2A):178-180.
[5]管才全,杨东升.人工免疫算法在空空导弹故障诊断中应用研究[J].设备管理与维修,2018,22(10):168-170.
[2]吴雪毅,李君芳.船舶网络中的高精度入侵检测方法设计[J].舰船科学技术,2018,40(5A):157-159.
[3]黄超.云计算下船舶网络入侵高精度检测方法研究[J].舰船科学技术,2018,40(6A):130-132.
[4]陈志忠.船舶监控网络入侵检测系统设计[J].舰船科学技术,2018,40(2A):178-180.
[5]管才全,杨东升.人工免疫算法在空空导弹故障诊断中应用研究[J].设备管理与维修,2018,22(10):168-170.