{"product_id":"multi-fractal-traffic-and-anomaly-detection-in-computer-communications-9781032408460","title":"Multi-Fractal Traffic and Anomaly Detection in Computer Communications","description":"\u003cp\u003e • Author(s): Ming Li\u003cbr\u003e • Publisher: Taylor \u0026amp; Francis\u003cbr\u003e • Publisher Imprint: CRC Press\u003cbr\u003e • BISAC: Networking - General\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThis 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.\u003c\/p\u003e\u003cp\u003eProving 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.\u003c\/p\u003e\u003cp\u003eScholars and graduates studying network traffic in computer science will find the book beneficial.\u003c\/p\u003e","brand":"Taylor \u0026 Francis","offers":[{"title":"Hardcover","offer_id":45242196033687,"sku":"9781032408460","price":7057.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9781032408460.webp?v=1769231351","url":"https:\/\/atlanticbooks.com\/products\/multi-fractal-traffic-and-anomaly-detection-in-computer-communications-9781032408460","provider":"Atlantic Books","version":"1.0","type":"link"}