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YATA: Yet Another Proposal for Traffic Analysis and Anomaly Detection

Yu Wang1,2,*, Yan Cao2, Liancheng Zhang2, Hongtao Zhang3, Roxana Ohriniuc4, Guodong Wang5, Ruosi Cheng6

Henan University of Engineering, Xinzheng, 451191, China.
China National Digital Switching System Engineering & Technological R&D Center, Zhengzhou, 450002, China.
Zhengzhou University, Zhengzhou, 450001, China.
Florida Atlantic University, Boca Raton, FL 33341, USA.
Massachusetts College of Liberal Arts, North Adams, MA 01247, USA
Luoyang Electronic Equipment Test Center of China, Luoyang, 471003, China.

* Corresponding Author: Yu Wang. Email: email.

Computers, Materials & Continua 2019, 60(3), 1171-1187.


Network traffic anomaly detection has gained considerable attention over the years in many areas of great importance. Traditional methods used for detecting anomalies produce quantitative results derived from multi-source information. This makes it difficult for administrators to comprehend and deal with the underlying situations. This study proposes another method to yet determine traffic anomaly (YATA), based on the cloud model. YATA adopts forward and backward cloud transformation algorithms to fuse the quantitative value of acquisitions into the qualitative concept of anomaly degree. This method achieves rapid and direct perspective of network traffic. Experimental results with standard dataset indicate that using the proposed method to detect attacking traffic could meet preferable and expected requirements.


Cite This Article

Y. Wang, Y. Cao, L. Zhang, H. Zhang, R. Ohriniuc et al., "Yata: yet another proposal for traffic analysis and anomaly detection," Computers, Materials & Continua, vol. 60, no.3, pp. 1171–1187, 2019.


cc 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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