The emergency decision support system proposed in this paper uses data mining technology to analyze and mine a large amount of dynamic operation data and historical operation data in the China-ASEAN natural disaster database, which can be used to analyze the dynamic safety risk and optimize the emergency rescue and disposal plan for China-ASEAN natural disasters. In order to optimize the emergency decision support system, the core algorithm of data mining in the system is improved, an improved sequence analysis algorithm is proposed, and improvement measures are proposed on the basis of the inadequacy of the original Apriori algorithm. Through examples, the data mining algorithm’s specific process of automatically generating response suggestions for security events is demonstrated. The analysis of the data shows that the test results meet the expected results, and the algorithm can effectively make response decisions. The average false detection rate is only 8.05%. In scenarios 2, 3, and 4, all of them have higher emergency response efficiency, respectively, of 0.4445, 0.4616, and 0.5299. The completion time of the emergency response increases as the response level increases.