Ming Li

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

• Format: PDF

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.

Proving that mono-fractal LRD time series is ergodic, the book exhibits that LRD traffic is stationary. The author shows that the stationarity of multi-fractal traffic relies on observation time scales, and proposes multi-fractional generalized Cauchy processes and modified multi-fractional Gaussian noise. The book also establishes a set of guidelines for determining the record length of traffic in measurement. Moreover, it presents an approach of traffic simulation, as well as the anomaly detection of traffic under distributed-denial-of service attacks.

Scholars and graduates studying network traffic in computer science will find the book beneficial.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 296
• Erscheinungstermin: 29. Dezember 2022
• Englisch
• ISBN-13: 9781000817898
• Artikelnr.: 66934607

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