Complex communication application identification and private network mining technology under a large-scale network
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S.I. : SPIOT 2020
Complex communication application identification and private network mining technology under a large-scale network Chengshun Huang1,2 • Zijiang Zhu3,4 Received: 16 July 2020 / Accepted: 10 October 2020 Ó Springer-Verlag London Ltd., part of Springer Nature 2020
Abstract The emergence of the Internet has brought great convenience to people, changing the way of life in many fields, such as food, clothing, housing and transportation. With the increasing popularity of the Internet and the rapid development of network technology, the Internet has become the main communication tool and information sharing channel for people. Network users bring not only convenience but also great challenges to network. The purpose is to study the practicability of statistical protocol recognition methods in network environment and to develop new solutions based on the existing protocol recognition methods. Based on the method step by step to study the identification of a complex application (CA) problems, usability issues, put forward the solution, and the solution of complex application, puts forward a set of perfect CA identification and analysis framework, greatly improved the accuracy and efficiency of complex application, to more than 80%. While promoting the development of recognition technology, it solves problems and finally implements a recognition and analysis system for complex applications. The complex private network mining technology proposed in this paper solves many difficulties and challenges of CA identification and analysis in network environment and can effectively improve the network management capability of network operators. Keywords Protocol recognition Complex applications Data mining Private networks
1 Internet-based network Network protocol recognition technology refers to the extraction of key features that uniquely identify the protocol or application in network traffic through manual or
& Zijiang Zhu [email protected] Chengshun Huang [email protected] 1
Provincial Key Laboratory of Informational Service for Rural Area of Southwestern Hunan, Shaoyang University, Shaoyang 422000, Hunan, People’s Republic of China
2
College of Information Engineering, Shaoyang University, Shaoyang 422000, Hunan, People’s Republic of China
3
School of Information Science and Technology, South China Business College, Guangdong University of Foreign Studies, Guangzhou 510545, Guangdong, People’s Republic of China
4
Institute of Intelligent Information Processing, South China Business College, Guangdong University of Foreign Studies, Guangzhou 510545, Guangdong, People’s Republic of China
automated analysis of network traffic generated by the network protocol or application, and the one-to-one correspondence between traffic and protocol in the network based on these features. The commonly used protocol identification methods include port-based protocol identification method, load-based protocol identification method, statistics-based protocol identif
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