计算机科学 ›› 2021, Vol. 48 ›› Issue (11A): 565-569.doi: 10.11896/jsjkx.210100093
朱容辰1, 李欣1,2, 王晗旭1, 叶瀚1, 曹志威3, 樊志杰3
ZHU Rong-chen1, LI Xin1,2, WANG Han-xu1, YE Han1, CAO Zhi-wei3, FAN Zhi-jie3
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。
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