{"product_id":"ai-and-machine-learning-for-network-and-security-management-hardcover","title":"AI and Machine Learning for Network and Security Management - Hardcover","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eYulei Wu\u003c\/b\u003e (Author), \u003cb\u003eJingguo Ge\u003c\/b\u003e (Author), \u003cb\u003eTong Li\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003cb\u003eAI AND MACHINE LEARNING FOR NETWORK AND SECURITY MANAGEMENT\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003cb\u003eExtensive Resource for Understanding Key Tasks of Network and Security Management\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003ci\u003eAI and Machine Learning for Network and Security Management\u003c\/i\u003e covers a range of key topics of network automation for network and security management, including resource allocation and scheduling, network planning and routing, encrypted traffic classification, anomaly detection, and security operations. In addition, the authors introduce their large-scale intelligent network management and operation system and elaborate on how the aforementioned areas can be integrated into this system, plus how the network service can benefit. \u003c\/p\u003e\u003cp\u003eSample ideas covered in this thought-provoking work include: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003e How cognitive means, e.g., knowledge transfer, can help with network and security management\u003c\/li\u003e \u003cli\u003e How different advanced AI and machine learning techniques can be useful and helpful to facilitate network automation\u003c\/li\u003e \u003cli\u003e How the introduced techniques can be applied to many other related network and security management tasks\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003eNetwork engineers, content service providers, and cybersecurity service providers can use \u003ci\u003eAI and Machine Learning for Network and Security Management\u003c\/i\u003e to make better and more informed decisions in their areas of specialization. Students in a variety of related study programs will also derive value from the work by gaining a base understanding of historical foundational knowledge and seeing the key recent developments that have been made in the field.\u003c\/p\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eExtensive Resource for Understanding Key Tasks of Network and Security Management\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003ci\u003eAI and Machine Learning for Network and Security Management\u003c\/i\u003e covers a range of key topics of network automation for network and security management, including resource allocation and scheduling, network planning and routing, encrypted traffic classification, anomaly detection, and security operations. In addition, the authors introduce their large-scale intelligent network management and operation system and elaborate on how the aforementioned areas can be integrated into this system, plus how the network service can benefit. \u003c\/p\u003e\u003cp\u003eSample ideas covered in this thought-provoking work include: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003e How cognitive means, e.g., knowledge transfer, can help with network and security management\u003c\/li\u003e \u003cli\u003e How different advanced AI and machine learning techniques can be useful and helpful to facilitate network automation\u003c\/li\u003e \u003cli\u003e How the introduced techniques can be applied to many other related network and security management tasks\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003eNetwork engineers, content service providers, and cybersecurity service providers can use \u003ci\u003eAI and Machine Learning for Network and Security Management\u003c\/i\u003e to make better and more informed decisions in their areas of specialization. Students in a variety of related study programs will also derive value from the work by gaining a base understanding of historical foundational knowledge and seeing the key recent developments that have been made in the field.\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eYulei Wu, \u003c\/b\u003e is a Senior Lecturer with the Department of Computer Science, Faculty of Environment, Science and Economy, University of Exeter, UK. His research focuses on networking, Internet of Things, edge intelligence, information security, and ethical AI. He serves as an Associate Editor for IEEE Transactions on Network and Service Management, and IEEE Transactions on Network Science and Engineering, as well as an Editorial Board Member of Computer Networks, Future Generation Computer Systems, and Nature Scientific Reports at Nature Portfolio. He is a Senior Member of the IEEE and the ACM, and a Fellow of the HEA (Higher Education Academy). \u003c\/p\u003e\u003cp\u003e\u003cb\u003eJingguo Ge, \u003c\/b\u003e is currently a Professor of the Institute of Information Engineering, Chinese Academy of Sciences (CAS), and also a Professor of School of Cyber Security, University of Chinese Academy of Sciences. His research focuses on Future Network Architecture, 5G\/6G, Software-defined networking (SDN), Cloud Native networking, Zero Trust Architecture. He has published more than 60 research papers and is the holder of 28 patents. He participated in the formulation of 3 ITU standards on IMT2020. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eTong Li, \u003c\/b\u003e is currently a Senior Engineer of Institute of Information Engineering at the Chinese Academy of Sciences (CAS). His research and engineering focus on Computer Networks, Cloud Computing, Software-Defined Networking (SDN), and Distributed Network and Security Management. He participated 2 ITU standards on IMT2020 and developed many large-scale software systems on SDN, network management and orchestration.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 304\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.69 x 9 x 6 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e November 08, 2022\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":47213408256249,"sku":"9781119835875","price":180.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/2782\/3097\/files\/U09lUjg4K2poelJlSmxCU29vOVdkZz09.webp?v=1768104761","url":"https:\/\/bookscloud.io\/products\/ai-and-machine-learning-for-network-and-security-management-hardcover","provider":"BooksCloud Book Dropshipping","version":"1.0","type":"link"}