Visual Analysis of Multisource Heterogeneous Data Based on Improved DPCA Algorithm

This paper proposes a multiview collaborative visual analysis system of network security based on a DPCA (clustering by fast search and find of density peaks) clustering algorithm called DPCANETVis, with network security analysis requirements for multisource heterogeneous data. Firstly, the system p...

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Published in:Mathematical problems in engineering Vol. 2022; pp. 1 - 10
Main Authors: Zhou, Yun, Mengfei, Wen, Youzhi, He, Yun, Cheng, Jinhui, Lv, Yi, Zuo
Format: Journal Article
Language:English
Published: New York Hindawi 06.12.2022
John Wiley & Sons, Inc
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ISSN:1024-123X, 1563-5147
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Abstract This paper proposes a multiview collaborative visual analysis system of network security based on a DPCA (clustering by fast search and find of density peaks) clustering algorithm called DPCANETVis, with network security analysis requirements for multisource heterogeneous data. Firstly, the system proposes an improved DPCA clustering algorithm based on the hierarchical relationship of mail sending and receiving to achieve the purpose of accurate classification. Secondly, a three-layer visual layout is designed to display relevant information such as data hierarchy, node relationship, behavior model, and other relevant information, by mixing a variety of interactive visual analysis methods such as tree diagram, word cloud, line diagram, subject river, and parallel coordinate. Lastly, based on the exploration of events, all suspicious nodes and their abnormal behaviors can be displayed in the system. Finally, the prototype system is used to analyze the network security log data set provided by the ChinaVis 2018, and the feasibility of the multilevel interactive visual analysis method for network security is verified through many experiments and discussions.
AbstractList This paper proposes a multiview collaborative visual analysis system of network security based on a DPCA (clustering by fast search and find of density peaks) clustering algorithm called DPCANETVis, with network security analysis requirements for multisource heterogeneous data. Firstly, the system proposes an improved DPCA clustering algorithm based on the hierarchical relationship of mail sending and receiving to achieve the purpose of accurate classification. Secondly, a three-layer visual layout is designed to display relevant information such as data hierarchy, node relationship, behavior model, and other relevant information, by mixing a variety of interactive visual analysis methods such as tree diagram, word cloud, line diagram, subject river, and parallel coordinate. Lastly, based on the exploration of events, all suspicious nodes and their abnormal behaviors can be displayed in the system. Finally, the prototype system is used to analyze the network security log data set provided by the ChinaVis 2018, and the feasibility of the multilevel interactive visual analysis method for network security is verified through many experiments and discussions.
Author Jinhui, Lv
Yi, Zuo
Zhou, Yun
Mengfei, Wen
Yun, Cheng
Youzhi, He
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10.1016/j.ins.2013.04.009
10.1007/s12650-014-0213-6
10.3724/sp.j.1016.2011.00856
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10.1109/2945.468391
10.3778/j.issn.1673-9418.1312039
10.3778/j.issn.1673-9418.1707064
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Copyright Copyright © 2022 Yun Zhou et al.
Copyright © 2022 Yun Zhou et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0
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SubjectTerms Algorithms
Behavior
Clustering
Data mining
Graphical representations
Mathematical problems
Network security
Security
Systems design
Visualization
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