Covert attacks and honeypot defense on video surveillance systems

Huang Menglan1a,1b
Xie Xiaolan1a,1b
Tang Yang2
Yuan Tianwei3,4
Chen Chaoquan1a,1b
Lyu Shichao3,4
Zhang Weidong3,4
Sun Limin3,4
1. a. College of Information Science & Engineering, b. Guangxi Key Laboratory of Embedded Technology & Intelligent System, Guilin University of Technology, Guilin Guangxi 541006, China
2. Unit 61912, Beijing 100039, China
3. Beijing Key Laboratory of IoT Information Security Technology, Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China
4. School of Cyber Security, University of Chinese Academy of Sciences, Beijing 100049, China

Abstract

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.

Foundation Support

国家自然科学基金资助项目(62262011)
国家重点研发计划资助项目(2022YFC3301103)
广西自然科学基金资助项目(2021JJ170130)
CCF-质谱大模型基金资助项目(202225)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.09.0409
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 5
Section: Survey
Pages: 1301-1307
Serial Number: 1001-3695(2024)05-003-1301-07

Publish History

[2023-11-21] Accepted Paper
[2024-05-05] Printed Article

Cite This Article

黄梦兰, 谢晓兰, 唐扬, 等. 针对视频监控系统隐蔽式攻击及蜜罐防御 [J]. 计算机应用研究, 2024, 41 (5): 1301-1307. (Huang Menglan, Xie Xiaolan, Tang Yang, et al. Covert attacks and honeypot defense on video surveillance systems [J]. Application Research of Computers, 2024, 41 (5): 1301-1307. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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