基于大数据的模具制造网络流量异常检测与防御机制

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Bigdatabasednetworktrafficanomalydetectionand defense mechanism for mold manufacturing

LIUJing'，LIGuopeng²，HANKun²

（1.Information Network Center，Xi'an University of Posts& Telecommunications，Information，Xi'an 71O121，Shaanxi， China; 2.Test Center，National University of Defense Technology， Xi'an 71O106，Shaanxi， China）

Abstract： This paper focuses on the network security challenges in the digital transformation of mold manufacturing industry， and explores the network traffic anomaly detection and defense strategies based on big data technology. By integrating advanced technologies such as big data processing，machine learning， deep learning and generating countermeasure network （GAN），a comprehensive and intelligent network monitoring and protection system is constructed. This paper expounds the system framework from data collection to processing， analysis， detection and defense，and uses GAN technology to strengthen data and conduct confrontation training， thus improving the accuracy of anomaly detection and the intelligence of defense. Compared with the traditional support vector machine （SVM） algorithm，our method shows significant advantages in accuracy，recall，Fl score and detection ability of various attacks. This big data-based network traffic anomaly detection and defense scheme for mold manufacturing provides a practical and effective guarantee for the network security of the industry.

Key words： big data; mold manufacturing; network traffic; anomaly detection； defense mechanism

0 引言

模具作为工业生产中的基础工艺装备，其设计、制造及应用的效率与质量直接关系到整个产业链的竞争力和创新力[1]。（剩余6999字）