针对视频监控系统隐蔽式攻击及蜜罐防御

基于视频监控系统网络化和智能化发展带来的风险，研究其隐蔽式网络攻击问题，目的在于调研大量隐蔽式网络攻击案例，总结针对视频监控系统的隐蔽式攻击特异性。结合蜜罐技术在检测网络攻击行为和发现攻击线索等方面的独特优势，梳理针对视频监控系统隐蔽式攻击的蜜罐防御方法。针对监控视频蜜罐在视觉场景部署上的不足，介绍了一种深度场景伪造防御框架，将生成式AI大模型与视频监控蜜罐相结合。最后提出了面向视频监控系统的蜜罐防御技术的发展方向。

Covert attacks and honeypot defense on video surveillance systems

This paper investigated the issue of covert network attacks on video surveillance systems in light of their networking and intelligent development, which brought about new risks. The primary objective of this research was to explore numerous cases of covert network attacks and summarize the specific characteristics of such attacks targeting video surveillance systems. Additionally, this paper examined the unique advantages of honeypot technology in detecting network attack behaviors and identifying attack clues, and outlined the honeypot defense methods against covert attacks on video surveillance systems. Furthermore, considering the shortcomings in the visual scene deployment of video surveillance honeypots, this paper introduced a deep scene fabrication defense framework that combined generative AI models with video surveillance honeypots. Finally, it proposed the development direction of honeypot defense technology for video surveillance systems.