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计算机系统应用英文版:2023,32(2):226-233
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基于SNMP的拓扑增强识别算法
(东莞理工学院 网络空间安全学院, 东莞 523808)
SNMP-based Topology Enhanced Identification Algorithm
(School of Cyberspace Security, Dongguan University of Technology, Dongguan 523808, China)
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Received:June 13, 2022    Revised:September 07, 2022
中文摘要: 网络拓扑发现对于许多关键网络管理任务来说至关重要. 然而, 随着网络规模的不断增大, 网络结构的愈发复杂, 之前的基于SNMP的网络拓扑发现算法存在难以有效识别子网类型和多IP设备, 拓扑效率、准确率低等问题. 针对上述问题, 本文提出了基于SNMP的拓扑增强识别(SNMP-based topology enhanced identification, SNMP-TEI)算法. 首先, 启发式地确定子网IP地址并对其发送探针, 根据探测结果来判断子网类型, 在确定子网类型后及时终止探针注入防止网络负载过大; 其次通过MIB-II记录的系统信息设置设备指纹, 结合设备类型识别算法对终端主机IP进行设备指纹鉴定, 以达到识别多IP设备的目的. 实验结果表明, 此方法在仿真网络中可有效识别子网和多IP设备, 同时降低了网络负载, 探测准确率达到了96.43%.
Abstract:Network topology discovery is important for many key network management tasks. However, as the network scale expands, the network structure gets complex. The previous SNMP-based network topology discovery algorithms cannot effectively identify subnet types and multi-IP devices, and they have low topology efficiency and accuracy. In view of the above problems, this study proposes an SNMP-based topology enhancement identification (SNMP-TEI) algorithm. Firstly, the subnet IP address is heuristically determined, and probes are sent to it, so as to judge the subnet type according to the detection results. In addition, probe injection is stopped in a timely manner after the subnet type is determined, so as to prevent the network load from being too large. Secondly, the device fingerprint is set through system information recorded by MIB-II, and a device type identification algorithm is used to identify the device fingerprint of the terminal host IP, so as to identify multi-IP devices. The experimental results show that this method can effectively identify subnets and multi-IP devices in simulated networks and reduce the network load, with a detection accuracy of 96.43%.
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基金项目:国家重点研发计划(2021YFB3101300); 国家自然科学基金面上项目(61972089)
引用文本:
曾戈,李银,李睿.基于SNMP的拓扑增强识别算法.计算机系统应用,2023,32(2):226-233
ZENG Ge,LI Yin,LI Rui.SNMP-based Topology Enhanced Identification Algorithm.COMPUTER SYSTEMS APPLICATIONS,2023,32(2):226-233