融合多维标识特征的摄像头身份识别方法  

Camera Identity Recognition Method Fused with Multi-dimensional Identification Features

作　　者：朱容辰 李欣[1,2] 王晗旭 叶瀚 曹志威 樊志杰[3] ZHU Rong-chen;LI Xin;WANG Han-xu;YE Han;CAO Zhi-wei;FAN Zhi-jie(School of Information Network Security,People’s Public Security University of China,Beijing 100038,China;Key Laboratory of Security Prevention Technology and Risk Assessment of the Ministry of Public Security,Beijing 100026,China;Department of Information Security Technology,The Third Research Institute of Ministry of Public Security,Shanghai 200031,China)

机构地区：[1]中国人民公安大学信息网络安全学院,北京100038 [2]安全防范技术与风险评估公安部重点实验室,北京100026 [3]公安部第三研究所信息安全技术部,上海200031

出　　处：《计算机科学》2021年第S02期565-569,共5页Computer Science

基　　金：国家自然科学基金面上项目(62076246);公安部科技强警基础工作专项项目(2020GABJC01);中国人民公安大学拔尖创新人才培养经费支持研究生科研创新项目(2021yjsky016)。

摘　　要：随着智慧城市、公安大数据的发展,视频监控网络已成为城市治理的重要基础设施。但是,攻击者通过替换或篡改监控摄像头这一重要的前端设备,能够接入内部网络,实现设备劫持、信息窃取、网络瘫痪,威胁个人、社会与国家安全。为了提前识别非法或可疑的摄像头身份,提出了融合多维标识特征的摄像头身份识别方法。通过提取摄像头静态信息与动态流量信息,构建了融合显性、隐性、动态标识符的摄像头身份标识体系。为选择简洁有效的身份标识符,提出了基于自信息量与信息熵的标识符贡献度评估方法,所抽取的标识符特征向量能够为未来的异常摄像头入侵检测奠定基础。实验结果表明,显性标识符自信息量与贡献度最大,但容易被伪造;动态标识符贡献度次之,但流量收集与处理的工作量较大;静态标识符贡献度较低,但仍有一定的身份标识作用。With the development of smart cities and public security big data,video surveillance networks have become essential infrastructure for urban governance.However,by replacing or tampering with surveillance cameras-the important front-end device,an attacker can access the internal network to achieve device hijacking,information theft,network paralysis,and threatening personal,social,and national security.A camera identity recognition method combining multi-dimensional identification features is proposed to identify illegal camera identities in advance.A camera identification system that integrates explicit,implicit,and dynamic identifiers is constructed by extracting the camera’s static information and the dynamic flow information.An evaluation method of identifier contribution based on self-information and information entropy is proposed to select a concise and practical identity identifier.The extracted identifier feature vector can lay the foundation for future abnormal camera intrusion detection.Experimental results show that explicit identifiers have the most considerable amount of self-information and contribution but are easy to be forged;dynamic identifiers have the second-highest contribution,but the workload of traffic collection and processing is enormous;static identifiers have a low contribution but still have a specific role in identification.

关 键 词：摄像头 标识特征 自信息量 身份识别 入侵检测 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]