基于大模型技术的商烟物流工控安全优化研究OA

Aiming at the problems of high false alarm rate,rigid strategy,insufficient operation and maintenance,and lack of closed-loop in the traditional industrial control security protection system of the commercial tobacco logistics center,this article takes the industrial control system of the center as the research object,integrates large language model technology to construct a five layer closed-loop protection system of"perception-analysis-decision-response-optimization",integrates core technologies such as multi-source data fusion analysis and intelligent strategy dynamic configuration,and designs four functional modules.The research results show that after optimization,the false alarm rate of the system has been reduced to 4.8％,the accuracy of anomaly recognition has reached 96.2％,the response time to security incidents has been shortened by 75％,the duration of business interruption and the workload of operation and maintenance have been significantly reduced,which can effectively resist various common industrial control security attacks.The system is adapted to the characteristics of commercial tobacco logistics business,has repli-cability and scalability,and provides a practical template for upgrading the industrial control security protection in the tobacco industry.