FCM-GASVM-based industrial control system intrusion detection method

The invention relates to an FCM-GASVM-based industrial control system intrusion detection method, in particular, a CM-GASVM-based industrial control system application layer network intrusion detection method. According to the method, unsupervised fuzzy C-mean clustering and a supervised support vector machine are combined so as to extract the communication traffic data of the Modbus/TCP of an industrial control system; FCM clustering is performed on the communication data; and a part of the data, which meet a threshold condition, are classified through a genetic algorithm optimized-support vector machine. Since unsupervised learning and supervised learning are combined together, training time can be effectively reduced with category labels not required to be known in advance, and classification accuracy can be improved. 本发明涉及基于FCM-GASVM的工业控制系统入侵检测方法，具体为基于FCM-GASVM算法提出了种工业控制系统应用层网络入侵检测方法，该方法将无监督的模糊C-均值聚类和有监督的支持向量机相结合，提取工业控制系统Modbus/TCP协议的通信流量数据，设计了种先将通信数据利用FCM聚类，后将满足阈值条件的部分数据进步由遗传算法优化的支持向量机分类的方法。该方法将无监督学习和有监督