MATEC Web Conf.
Volume 309, 20202019 International Conference on Computer Science Communication and Network Security (CSCNS2019)
|Number of page(s)||13|
|Section||Smart Algorithms and Recognition|
|Published online||04 March 2020|
Overview of clustering analysis algorithms in unknown protocol recognition
Communication and Network Laboratory (Dalian University), No.10 xuefu street, Dalian economic and technological development zone, liaoning, Dalian 116622, China
* Corresponding author: firstname.lastname@example.org
In the process of identifying unknown protocol of bit stream, the clustering of data sets of bit stream in the protocol is the basis of further identifying unknown protocol. Therefore, on the one hand, this paper analyses the classical clustering algorithms used in unknown protocol recognition from three perspectives: the whole process of clustering analysis, similarity measurement and clustering result evaluation. On the other hand, the development trend of clustering algorithm in unknown protocol recognition is summarized, and other problems in unknown protocol recognition can be solved by clustering algorithm according to the characteristics of bit stream data set, which can provide reference for future research work. Finally, the challenges faced by the Research Institute and the prospects for future work are given.
Key words: Unknown protocol recognition / Cluster analysis / Similarity measure / Bit stream
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.