{"product_id":"multifractal-traffic-and-anomaly-detection-in-computer-communications-9781032408460","title":"Multi-Fractal Traffic and Anomaly Detection in Computer Communications","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003eThis book provides a comprehensive theory of mono- and multi-fractal traffic, including ergodicity, predictability, modeling, simulation, stationarity tests, traffic measurement, and anomaly detection. It demonstrates that mono-fractal LRD time series is ergodic and proposes multi-fractional generalized Cauchy processes and modified multi-fractional Gaussian noise. It also establishes guidelines for determining the record length of traffic and presents an approach to traffic simulation and anomaly detection under distributed-denial-of-service attacks. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Hardback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 282 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 29 December 2022\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Taylor \u0026amp; Francis Ltd\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eThis comprehensive book delves into the intricate realm of mono- and multi-fractal traffic, offering a thorough theoretical framework that encompasses a wide range of topics. It begins by introducing the fundamentals of long-range dependent time series and 1\/f noise, providing a solid foundation for understanding the dynamics of traffic. The author then explores the ergodicity and predictability of traffic, shedding light on the patterns and behaviors that govern traffic flow. Moving forward, the book delves into traffic modeling and simulation, employing advanced techniques to accurately represent and analyze traffic patterns. It discusses various traffic measurement methods and highlights the significance of anomaly detection in communications networks.\u003cbr\u003e\u003cbr\u003eIn order to demonstrate the ergodicity of mono-fractal LRD time series, the author showcases that LRD traffic exhibits stationary behavior. Furthermore, the author demonstrates that the stationarity of multi-fractal traffic relies on the observation time scales, proposing multi-fractional generalized Cauchy processes and modified multi-fractional Gaussian noise to capture the complex dynamics of traffic. Additionally, the book establishes a set of guidelines for determining the appropriate record length of traffic in measurement, ensuring accurate and reliable data analysis.\u003cbr\u003e\u003cbr\u003eFurthermore, the book presents an innovative approach to traffic simulation, enabling researchers and practitioners to study traffic behavior in a controlled environment. Moreover, it addresses the critical issue of traffic anomaly detection under distributed-denial-of-service attacks, providing valuable insights into defending against cyber threats in modern networks.\u003cbr\u003e\u003cbr\u003eThis book is a valuable resource for scholars and graduates pursuing advanced studies in network traffic in computer science. It offers a comprehensive and up-to-date understanding of the latest research and developments in the field, equipping readers with the tools and knowledge necessary to excel in their academic and professional endeavors.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 714g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 260 x 182 x 23 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9781032408460\u003c\/p\u003e","brand":"Ming Li","offers":[{"title":"Hardback","offer_id":44104738406650,"sku":"9781032408460","price":75.14,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/noImage_1_017f3399-b1a0-4112-bf45-cde03b399eeb.jpg?v=1676912949","url":"https:\/\/shulphink.com\/products\/multifractal-traffic-and-anomaly-detection-in-computer-communications-9781032408460","provider":"Shulph Ink","version":"1.0","type":"link"}