摘要
针对传统的光纤传感网络入侵检测系统,在大数据环境下存在检测时间过长、检测率偏低、误报率较高等问题,设计基于大数据的光纤传感网络入侵检测系统。虚拟机主要利用PC机模拟一个网络设备,将客户操作系统的光纤传感网络设备连接到PC机的网桥上,通过PC机实现光纤传感网络设备的虚拟。在大数据的环境下,将光纤传感网络入侵检测系统与虚拟化的网络特征相结合,利用Xen的半虚拟技术,实现大数据下的光纤传感网络入侵检测。实验结果表明,该检测系统能够快速、准确检测出光纤传感网络数据中存在的入侵数据,同时检测误报率不到4%,说明所提系统具有更好的性能。
Aiming at the traditional optical fiber sensing network data intrusion detection system,in the big data environment,there are problems such as long detection time,low detection rate and high false positive rate.The data intrusion detection system based on big data is designed.The virtual machine mainly uses a PC to simulate a network device,connects the optical fiber sensing network device of the guest operating system to the bridge of the PC,and realizes the virtualization of the optical fiber sensing network device through the PC.In the context of big data,the optical sensor network data intrusion detection system is combined with the virtualized network features,and Xen’s semi-virtual technology is used to realize data intrusion detection of optical fiber sensing networks under big data.The experimental results show that the detection system can quickly and accurately detect the intrusion data existing in the fiber sensor network data,and the detection false alarm rate is less than 4%,indicating that the proposed system has better performance.
作者
孟小冬
冯锋
MENG Xiaodong;FENG Feng(School of Computing,Hulunbuir College,Inner Mongolia 021000,China;School of Information Engineering,Ningxia University,Ningxia 750000,China)
出处
《激光杂志》
北大核心
2019年第8期98-101,共4页
Laser Journal
基金
宁夏重点研发计划重点项目(No.2018BFG02003)
关键词
大数据
光纤传感网络
入侵
检测系统
big data
optical fiber sensing network
data intrusion
detection system
