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Filters: Author is Wu, Weidong  [Clear All Filters]
2020-10-16
Tian, Zheng, Wu, Weidong, Li, Shu, Li, Xi, Sun, Yizhen, Chen, Zhongwei.  2019.  Industrial Control Intrusion Detection Model Based on S7 Protocol. 2019 IEEE 3rd Conference on Energy Internet and Energy System Integration (EI2). :2647—2652.

With the proposal of the national industrial 4.0 strategy, the integration of industrial control network and Internet technology is getting higher and higher. At the same time, the closeness of industrial control networks has been broken to a certain extent, making the problem of industrial control network security increasingly serious. S7 protocol is a private protocol of Siemens Company in Germany, which is widely used in the communication process of industrial control network. In this paper, an industrial control intrusion detection model based on S7 protocol is proposed. Traditional protocol parsing technology cannot resolve private industrial control protocols, so, this model uses deep analysis algorithm to realize the analysis of S7 data packets. At the same time, in order to overcome the complexity and portability of static white list configuration, this model dynamically builds a white list through white list self-learning algorithm. Finally, a composite intrusion detection method combining white list detection and abnormal behavior detection is used to detect anomalies. The experiment proves that the method can effectively detect the abnormal S7 protocol packet in the industrial control network.