EconPapers    
Economics at your fingertips  
 

FRACTAL CHARACTERISTICS OF NETWORK TRAFFIC AND ITS CORRELATION WITH NETWORK SECURITY

Caichang Ding, Yiqin Chen, Zhiyuan Liu, Ahmed Mohammed Alshehri () and Tianyin Liu
Additional contact information
Caichang Ding: School of Computer Science, Hubei Polytechnic University, Huangshi 435003, P. R. China
Yiqin Chen: ��School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, P. R. China
Zhiyuan Liu: School of Computer Science, Hubei Polytechnic University, Huangshi 435003, P. R. China
Ahmed Mohammed Alshehri: ��Nonlinear Analysis and Applied, Mathematics (NAAM)-Research Group, Department of Mathematics, Faculty of Science, King Abdulaziz University, P. O. Box 80203, Jeddah 21589, Saudi Arabia
Tianyin Liu: School of Computer Science, Hubei Polytechnic University, Huangshi 435003, P. R. China

FRACTALS (fractals), 2022, vol. 30, issue 02, 1-11

Abstract: Based on the analysis of the self-similarity of network traffic, a network anomaly detection technology is proposed by combining with the fuzzy logic so as to explore the fractal characteristics of network traffic. The concepts of network traffic and network security are introduced. Then, a network traffic model of network traffic is proposed based on the fractal theory and wavelet analysis. Finally, a distributed denial of service (DDoS) that attacks the monitoring and intensity judgment method is put forward based on the fuzzy logic theory. The results show that the autocorrelation function of the multifractal wavelet model constructed based on the local Hurst exponent (LHE) can reach a mean square error (MSE) of 4.762 × 10−4, which proves that the network traffic model proposed can reduce the impact of the non-stationary characteristics of the network traffic on the modeling accuracy. The network security detection method proposed can monitor the DDoS attacks and can accurately judge the attack intensity in real time. The research in this study provides an important reference for the scientific operation of the network.

Keywords: Network Traffic; Fractal Characteristics; Self-Similarity; Network Security; Network Anomaly Detection (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0218348X22400679
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:fracta:v:30:y:2022:i:02:n:s0218348x22400679

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0218348X22400679

Access Statistics for this article

FRACTALS (fractals) is currently edited by Tara Taylor

More articles in FRACTALS (fractals) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().

 
Page updated 2025-03-20
Handle: RePEc:wsi:fracta:v:30:y:2022:i:02:n:s0218348x22400679