연구 분야: Safety
학회: CIBDA '25: Proceedings of the 2025 6th International Conference on Computer Information and Big Data Applications
With the large-scale deployment of industrial control system, network security has become an urgent problem to be solved. This study uses big data analysis technology to build a security protection system to improve the recognition and response ability of industrial control system to network threats. The system collects and analyzes a large amount of data generated by the operation of industrial control systems, and uses cutting-edge data analysis methods to accurately identify abnormal behaviors and potential security threats. The efficiency of deep learning algorithm in threat detection and response mechanism is deeply discussed in order to improve the accuracy of threat identification and the efficiency of security protection. Experiments show that the system design is feasible and effective, which can effectively strengthen the network security defense of industrial control system, greatly reduce the potential security risks, and effectively promote the development of network security protection technology of industrial control system.
| 발행 연도 | 2025년 |
|---|---|
| 인용수 | 0 |
| 출판 국가 | China |
| 사이트 | ACM |
| 좋아요 수 | 0 |