Multi-Fractal Traffic and Anomaly Detection in Computer Communications

<p>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.</p><p>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.</p><p>Scholars and graduates studying network traffic in computer science will find the book beneficial.</p>