The attacks against the industrial control network have different types and various attack intensity. Under this circumstance, the traditional detection techniques cannot identify the multiple types of attacks effectively, and can not assess the security situations of the industrial control network comprehensively and accurately. Therefore, the industrial control network security situation awareness model is proposed. Firstly, the rule extraction can be done by applying the improved C-SVC algorithm to the multi-sensor data. Then with the application of decision fusion algorithm, the decision-level fusion is completed and the results of situation awareness are procured. The simulation experiment results show that the proposed model and algorithms can distinguish multiple types of attacks effectively, identify the attacks that are launched against the industrial control system accurately, and generate the results of situation awareness.