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The Research of Address Message of an Unknown Single Protocol Data Frame

Zheng Jiea,b, Li Jianpinga

a School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China;
b Chongqing College of Electronic Engineering, Chongqing College Town, Chongqing, China

* Corresponding Author: Zheng Jie, email

Intelligent Automation & Soft Computing 2018, 24(1), 139-144. https://doi.org/10.1080/10798587.2016.1267445

Abstract

Network protocols are sets of standards for certain network communications. The identification and analysis of network protocol are of significance to network management and security. There are various technologies of protocol identification, but in the process of identification protocols, in order to simplify the identification process and improve the efficiency of protocol identification, unknown mixed multi-protocol needs to be separated into single protocol so as to make further identification. This paper presents an efficient method to determine the single protocol address message based on the previous research of separating unknown mixed data frame into single protocol. By this way, the data frames of single protocol are split into point-to-point data frame according to the address; consequently, the final identification of unknown protocol can be realized. Moreover, the method was evaluated by analysis of the ARP and TCP data; this method is able to find the more than 2/3 of address information.

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Cite This Article

APA Style
Jie, Z., Jianping, L. (2018). The research of address message of an unknown single protocol data frame. Intelligent Automation & Soft Computing, 24(1), 139-144. https://doi.org/10.1080/10798587.2016.1267445
Vancouver Style
Jie Z, Jianping L. The research of address message of an unknown single protocol data frame. Intell Automat Soft Comput . 2018;24(1):139-144 https://doi.org/10.1080/10798587.2016.1267445
IEEE Style
Z. Jie and L. Jianping, “The Research of Address Message of an Unknown Single Protocol Data Frame,” Intell. Automat. Soft Comput. , vol. 24, no. 1, pp. 139-144, 2018. https://doi.org/10.1080/10798587.2016.1267445



cc Copyright © 2018 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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