Design and research of network security threat detection and traceability system based on AI

Hui Wang; Xuelong Wang; Hua Wu; Heqing Wang; Lu Zhang; Qingpeng Zhang; Jing Wang

doi:10.1117/12.2622727

1 December 2021 Design and research of network security threat detection and traceability system based on AI

Hui Wang, Xuelong Wang, Hua Wu, Heqing Wang, Lu Zhang, Qingpeng Zhang, Jing Wang

Proceedings Volume 12079, Second IYSF Academic Symposium on Artificial Intelligence and Computer Engineering; 120790G (2021) https://doi.org/10.1117/12.2622727
Event: 2nd IYSF Academic Symposium on Artificial Intelligence and Computer Engineering, 2021, Xi'an, China

Abstract

The new generation of network security threats present a mixed and multi-stage attack mode. Using AI technology for accurate detection has gradually become a consensus in the field of network security. The paper briefly describes the background and research status of threat detection and traceability, puts forward a network security threat detection and traceability system based on AI, and designs the overall system architecture of network data acquisition and traffic processing, security threat detection engine, situational awareness and traceability evidence. According to different attack types, AI based detection engine is studied, and threat intelligent detection and location services for cyberspace and application system is developed by using cloud security service platform. Through AI detection, intelligence detection, anomaly detection and traffic gene detection, real-time monitoring, traceability analysis and emergency disposal of network security threats are realized. At the end of the paper, three typical threat detection application scenarios are recommended.

Citation Download Citation

Hui Wang, Xuelong Wang, Hua Wu, Heqing Wang, Lu Zhang, Qingpeng Zhang, and Jing Wang "Design and research of network security threat detection and traceability system based on AI", Proc. SPIE 12079, Second IYSF Academic Symposium on Artificial Intelligence and Computer Engineering, 120790G (1 December 2021); https://doi.org/10.1117/12.2622727

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