AI and machine learning for network and security management / Yulei Wu, Jingguo Ge and Tong Li
(IEEE Press series on networks and services management)
データ種別 | 電子ブック |
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出版者 | (Piscataway, New Jersey ; Hoboken, New Jersey : IEEE Press : Wiley) |
出版年 | [2023] |
大きさ | 1 online resource (338 pages) |
著者標目 | *Wu, Yulei author Ge, Jingguo author Li, Tong author |
書誌詳細を非表示
一般注記 | Intro -- Table of Contents -- Title Page -- Copyright -- Author Biographies -- Preface -- Acknowledgments -- Acronyms -- 1 Introduction -- 1.1 Introduction -- 1.2 Organization of the Book -- 1.3 Conclusion -- References -- 2 When Network and Security Management Meets AI and Machine Learning -- 2.1 Introduction -- 2.2 Architecture of Machine Learning-Empowered Network and Security Management -- 2.3 Supervised Learning -- 2.4 Semisupervised and Unsupervised Learning -- 2.5 Reinforcement Learning -- 2.6 Industry Products on Network and Security Management -- 2.7 Standards on Network and Security Management -- 2.8 Projects on Network and Security Management -- 2.9 Proof-of-Concepts on Network and Security Management -- 2.10 Conclusion -- References -- Notes -- 3 Learning Network Intents for Autonomous Network Management* -- 3.1 Introduction -- 3.2 Motivation -- 3.3 The Hierarchical Representation and Learning Framework for Intention Symbols Inference -- 3.4 Experiments -- 3.5 Conclusion -- References -- Notes -- 4 Virtual Network Embedding via Hierarchical Reinforcement Learning1 -- 4.1 Introduction -- 4.2 Motivation -- 4.3 Preliminaries and Notations -- 4.4 The Framework of VNE-HRL -- 4.5 Case Study -- 4.6 Related Work -- 4.7 Conclusion -- References -- Note -- 5 Concept Drift Detection for Network Traffic Classification -- 5.1 Related Concepts of Machine Learning in Data Stream Processing -- 5.2 Using an Active Approach to Solve Concept Drift in the Intrusion Detection Field -- 5.3 Concept Drift Detector Based on CVAE -- 5.4 Deployment and Experiment in Real Networks -- 5.5 Future Research Challenges and Open Issues -- 5.6 Conclusion -- References -- Note -- 6 Online Encrypted Traffic Classification Based on Lightweight Neural Networks* -- 6.1 Introduction -- 6.2 Motivation -- 6.3 Preliminaries -- 6.4 The Proposed Lightweight Model 6.5 Case Study -- 6.6 Related Work -- 6.7 Conclusion -- References -- Notes -- 7 Context-Aware Learning for Robust Anomaly Detection* -- 7.1 Introduction -- 7.2 Pronouns -- 7.3 The Proposed Method -- AllRobust -- 7.4 Experiments -- 7.5 Discussion -- 7.6 Conclusion -- References -- Note -- 8 Anomaly Classification with Unknown, Imbalanced and Few Labeled Log Data -- 8.1 Introduction -- 8.2 Examples -- 8.3 Methodology -- 8.4 Experimental Results and Analysis -- 8.5 Discussion -- 8.6 Conclusion -- References -- Notes -- 9 Zero Trust Networks -- 9.1 Introduction to Zero-Trust Networks -- 9.2 Zero-Trust Network Solutions -- 9.3 Machine Learning Powered Zero Trust Networks -- 9.4 Conclusion -- References -- 10 Intelligent Network Management and Operation Systems -- 10.1 Introduction -- 10.2 Traditional Operation and Maintenance Systems -- 10.3 Security Operation and Maintenance -- 10.4 AIOps -- 10.5 Machine Learning-Based Network Security Monitoring and Management Systems -- 10.6 Conclusion -- References -- 11 Conclusions, and Research Challenges and Open Issues -- 11.1 Conclusions -- 11.2 Research Challenges and Open Issues -- References -- Index -- End User License Agreement Description based on print version record Includes bibliographical references and index John Wiley and Sons Wiley Online Library: Complete oBooks HTTP:URL=https://onlinelibrary.wiley.com/doi/book/10.1002/9781119835905 |
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件 名 | LCSH:Computer networks -- Security measures -- Data processing
全ての件名で検索
LCSH:Artificial intelligence LCSH:Machine learning CSHF:R�eseaux d'ordinateurs -- S�ecurit�e -- Mesures -- Informatique 全ての件名で検索 CSHF:Intelligence artificielle CSHF:Apprentissage automatique FREE:artificial intelligence FREE:Artificial intelligence FREE:Machine learning |
分 類 | LCC:Q335 DC23:006.3 |
書誌ID | EB00004553 |
ISBN | 1119835909 |
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