Ming Li

Multi-Fractal Traffic and Anomaly Detection in Computer Communications (eBook, ePUB)

• Format: ePub

Produktbeschreibung

This book provides a comprehensive theory of mono- and multi-fractal traffic, including the basics of long-range dependent time series and 1/f noise, ergodicity and predictability of traffic, traffic modeling and simulation, stationarity tests of traffic, traffic measurement and the anomaly detection of traffic in communications networks.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 296
• Erscheinungstermin: 29. Dezember 2022
• Englisch
• ISBN-13: 9781000817904
• Artikelnr.: 66926738

Autorenporträt

Ming Li, PhD, is a professor at Ocean College, Zhejiang University and the East China Normal University. He has been a contributor for many years to the fields of computer science, mathematics, statistics, and mechanics. He has authored more than 200 articles and 5 monographs on the subjects.

Inhaltsangabe

1. Fractal time series 2. On 1/f noise 3. Power laws of fractal data in
cyber-physical networking systems 4. Ergodicity of long-range dependent
traffic 5. Predictability of long-range dependent series 6. Long-range
dependence and self-similarity of daily traffic with different protocols 7.
Stationarity test of traffic 8. Record length requirement of LRD traffic 9.
Multi-fractional generalized Cauchy process and its application to traffic
10. Modified multi-fractional Gaussian noise and its application to traffic
11. Traffic simulation 12. Reliably identifying signs of DDOS flood attacks
based on traffic pattern recognition 13. Change trend of Hurst parameter of
multi-scale traffic under DDOS flood attacks 14. Postscript