基于概念格的网络设备识别方法
|
摘要
网络技术正在深度改变经济与社会面貌,网络空间安全的重要性与日俱增。网络设备识别是网络安全策略重要的基础性工作,也是计算机网络研究的热点。识别网络设备的主要手段是探测目标设备开放的端口。探测获取的信息是一类典型的大数据,具有概念繁多、变化迅速和难以量化等特点,这给设备类型识别带来了较大困难。针对上述问题,提出了一种基于概念格的网络设备类型识别方法,可以显著简化识别过程,有效解决了设备差异程度难以量化的问题。
Network technology is profoundly changing the economic and social outlook, and the importance of cyberspace security is increasing. Network equipment identification is an important basic work of network security strategy, and it is also a hotspot of computer network research. The primary means of identifying a network device is to detect the open port of the target device. The information obtained by the detection is a kind of typical big data, which has many characteristics, rapid changes and difficulty in quantification, which brings great difficulty to device type identification. Aiming at the above problems, a recognition method based on concept lattice is proposed, which can significantly simplify the identification process and effectively solve the problem that the degree of device differentiation is difficult to quantify.
Network technology is profoundly changing the economic and social outlook, and the importance of cyberspace security is increasing. Network equipment identification is an important basic work of network security strategy, and it is also a hotspot of computer network research. The primary means of identifying a network device is to detect the open port of the target device. The information obtained by the detection is a kind of typical big data, which has many characteristics, rapid changes and difficulty in quantification, which brings great difficulty to device type identification. Aiming at the above problems, a recognition method based on concept lattice is proposed, which can significantly simplify the identification process and effectively solve the problem that the degree of device differentiation is difficult to quantify.
引文
[1]李富合.网络设备识别系统的设计与实现[D].北京:北京邮电大学,2012LI Fu-he.The Design and Implementation of Network Equipment Identification System[D].Beijing:Beijing University of Posts and Telecommunications,2012.
[2]张江,孙治,段梦军等.基于ICMP、UDP、TCP协议的分布式IP级拓扑探测方法[J].通信技术,2018,51(11):2645-2649.ZHANG Jiang,SUN Zhi,DUAN Mengjun,et al.Distributed IP-Level Topology Detection Method based on ICMP,UDP and TCP Protocols[J].Communications Technology,2018,51(11):2645-2649.
[3]Ganter B,Wille R.Formal Concept Analysis:Mathematical Foundations[M].Berlin:Springer,1999.
[4]钟利华,张素兰,胡立华等.基于概念格层次分析的视觉词典生成方法[J].计算机辅助设计与图形学学报,2015(1):136-141.ZHONG Li-hua,ZHANG Su-lan,HU Li-hua,et al.AConcept Lattice Hierarchy Based Generating Method of Visual Dictionary[J].Journal of Computer-Aided Design&Computer Graphics,2015(1):136-141.
[5]张磊,张宏莉,韩道军等.基于概念格的RBAC模型中角色最小化问题的理论与算法[J].电子学,2014,42(12):2371-2378.ZHANG Lei,ZHANG Hong-li,HAN Dao-jun,et al.Theory and Algorithm for Roles Minimization Problem in RBAC Based on Concept Lattice[J].Acta Electronica Sinica,2014,42(12):2371-2378.
[6]De Maio C,Fenza G,Loia V,et al.Hierarchical Web Resources Retrieval by Exploiting Fuzzy Formal Concept Analysis[J].Information Processing&Management,2012,48(3):399-418.
[7]李宏涛,何克清,王健等.基于概念格和随机游走的社交网朋友推荐算法[J].四川大学学报(工程科学版),2015,47(6):131-138.LI Hong-tao,HE Ke-qing,WANG Jian,et al.A Friends Recommendation Algorithm Based on Formal Concept Analysis and Random Walk in Social Network[J].Journal of Sichuan University(Engineering Science Edition),2015,47(6):131-138.
[8]蒋运承,李璞.一种面向形式概念分析的语义相似度计算框架[J].华南师范大学学报(自然科学版),2016,48(3):44-52.JIANG Yun-cheng,LI Pu.A Framework for Semantic Similarity Estimation in Formal Concept Analysis[J].Journal of South China Normal University(Natural Science Edition),2016,48(3):44-52.
[9]Kaytoue M,Kuznetsov S O,Napoli A,et al.Mining Gene Expression Data with Pattern Structures in Formal Concept Analysis[J].Information Sciences,2011,181(10):1989-2001.
[2]张江,孙治,段梦军等.基于ICMP、UDP、TCP协议的分布式IP级拓扑探测方法[J].通信技术,2018,51(11):2645-2649.ZHANG Jiang,SUN Zhi,DUAN Mengjun,et al.Distributed IP-Level Topology Detection Method based on ICMP,UDP and TCP Protocols[J].Communications Technology,2018,51(11):2645-2649.
[3]Ganter B,Wille R.Formal Concept Analysis:Mathematical Foundations[M].Berlin:Springer,1999.
[4]钟利华,张素兰,胡立华等.基于概念格层次分析的视觉词典生成方法[J].计算机辅助设计与图形学学报,2015(1):136-141.ZHONG Li-hua,ZHANG Su-lan,HU Li-hua,et al.AConcept Lattice Hierarchy Based Generating Method of Visual Dictionary[J].Journal of Computer-Aided Design&Computer Graphics,2015(1):136-141.
[5]张磊,张宏莉,韩道军等.基于概念格的RBAC模型中角色最小化问题的理论与算法[J].电子学,2014,42(12):2371-2378.ZHANG Lei,ZHANG Hong-li,HAN Dao-jun,et al.Theory and Algorithm for Roles Minimization Problem in RBAC Based on Concept Lattice[J].Acta Electronica Sinica,2014,42(12):2371-2378.
[6]De Maio C,Fenza G,Loia V,et al.Hierarchical Web Resources Retrieval by Exploiting Fuzzy Formal Concept Analysis[J].Information Processing&Management,2012,48(3):399-418.
[7]李宏涛,何克清,王健等.基于概念格和随机游走的社交网朋友推荐算法[J].四川大学学报(工程科学版),2015,47(6):131-138.LI Hong-tao,HE Ke-qing,WANG Jian,et al.A Friends Recommendation Algorithm Based on Formal Concept Analysis and Random Walk in Social Network[J].Journal of Sichuan University(Engineering Science Edition),2015,47(6):131-138.
[8]蒋运承,李璞.一种面向形式概念分析的语义相似度计算框架[J].华南师范大学学报(自然科学版),2016,48(3):44-52.JIANG Yun-cheng,LI Pu.A Framework for Semantic Similarity Estimation in Formal Concept Analysis[J].Journal of South China Normal University(Natural Science Edition),2016,48(3):44-52.
[9]Kaytoue M,Kuznetsov S O,Napoli A,et al.Mining Gene Expression Data with Pattern Structures in Formal Concept Analysis[J].Information Sciences,2011,181(10):1989-2001.