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AI and Machine Learning for Network and Security Management
| AI and Machine Learning for Network and Security Management |
| Autore | Ge Jingguo |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2022 |
| Descrizione fisica | 1 online resource (338 pages) |
| Altri autori (Persone) |
LiTong
WuYulei |
| Collana | IEEE Press Series on Networks and Service Management Ser. |
| ISBN |
1-119-83590-9
1-119-83589-5 1-119-83588-7 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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. |
| Record Nr. | UNINA-9910623986003321 |
Ge Jingguo
|
||
| Newark : , : John Wiley & Sons, Incorporated, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
AI and machine learning for network and security management / / Yulei Wu, Jingguo Ge and Tong Li
| AI and machine learning for network and security management / / Yulei Wu, Jingguo Ge and Tong Li |
| Autore | Wu Yulei |
| Pubbl/distr/stampa | Piscataway, New Jersey ; ; Hoboken, New Jersey : , : IEEE Press : , : Wiley, , [2023] |
| Descrizione fisica | 1 online resource (338 pages) |
| Disciplina | 006.3 |
| Collana | IEEE Press series on networks and services management |
| Soggetto topico |
Computer networks - Security measures - Data processing
Artificial intelligence Machine learning |
| ISBN |
1-119-83590-9
1-119-83589-5 1-119-83588-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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. |
| Record Nr. | UNINA-9910830309403321 |
|
Wu Yulei
|
||
| Piscataway, New Jersey ; ; Hoboken, New Jersey : , : IEEE Press : , : Wiley, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Essays in honor of Cheng Hsiao / / edited by Tong Li, M. Hashem Pesaran, Dek Terrell
| Essays in honor of Cheng Hsiao / / edited by Tong Li, M. Hashem Pesaran, Dek Terrell |
| Pubbl/distr/stampa | Bingley, England : , : Emerald Publishing, , [2020] |
| Descrizione fisica | 1 online resource (x, 457 pages) : illustrations |
| Disciplina | 330.015195 |
| Collana | Advances in econometrics |
| Soggetto topico | Econometrics |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-78973-957-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910480723703321 |
| Bingley, England : , : Emerald Publishing, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Essays in honor of Cheng Hsiao / / edited by Tong Li, M. Hashem Pesaran, Dek Terrell
| Essays in honor of Cheng Hsiao / / edited by Tong Li, M. Hashem Pesaran, Dek Terrell |
| Pubbl/distr/stampa | Bingley, England : , : Emerald Publishing, , [2020] |
| Descrizione fisica | 1 online resource (x, 457 pages) : illustrations |
| Disciplina | 330.015195 |
| Collana | Advances in econometrics |
| Soggetto topico | Econometrics |
| ISBN | 1-78973-957-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction / Dek Terrell, Tong Li and M. Hashem Pesaran -- Chapter 1. Correction for the Asymptotical Bias of the Arellano-Bond Type GMM Estimation of Dynamic Panel Models / Yonghui Zhang and Qiankun Zhou -- Chapter 2. Testing Convergence Using HAR Inference / Jianning Kong, Peter C.B. Phillips and Donggyu Sul -- Chapter 3. Model Selection for Explosive Models / Yubo Tao and Jun Yu -- Chapter 4. A VAR Approach to Forecasting Multivariate Long Memory Processes Subject to Structural Breaks / Cindy S.H. Wang and Shui Ki Wan -- Chapter 5. Identifying Global and National Output and Fiscal Policy Shocks Using a GVAR / Alexander Chudik, M Hashem Pesaran and Kamiar Mohaddes -- Chapter 6. The Determinants of Health Care Expenditure and Trends: A Semiparametric Panel Data Analysis of OECD Countries / Ming Kong, Jiti Gao and Xueyan Zhao -- Chapter 7. Growth Empirics: A Bayesian Semiparametric Model with Random Coefficients for a Panel of OECD Countries / Badi H. Baltagi, Georges Bresson and Jean-Michel Etienne -- Chapter 8. Robust Estimation and Inference for Importance Sampling Estimators with Infinite Variance / Joshua C.C. Chan, Chenghan Hou and Thomas Tao Yang -- Chapter 9. Econometrics of Scoring Auctions / Jean-Jacques Laffont, Isabelle Perrigne, Michel Simioni and Quang Vuong -- Chapter 10. Bayesian Estimation of Linear Sum Assignment Problems / Yu-Wei Hsieh and Mathew Shum -- Chapter 11. The Mode ls the Message: Using Predata as Exclusion Restrictions to Evaluate Survey Design / Heng Chen, Geoffrey Dunbar and Q. Rallye Shen -- Chapter 12. Estimating Peer Effects on Career Choice : a Spatial Multinomial Logit Approach / Bolun Li, Robin Sickles and Jenny Williams -- Chapter 13. Mortgage Portfolio Diversification in the Presence of Cross-sectional and Spatial Dependence / Timothy Dombrowski, R. Kelley Pace and Rajesh P. Narayanan -- Chapter 14. An Econometrician's Perspective on Big Data / Cheng Hsiao -- Chapter 15. Comments on "An Econometrician's Perspective on Big Data" by Cheng Hsiao / Thomas B. Fomby -- Chapter 16. Comments on "An Econometrician's Perspective on Big Data" by Cheng Hsiao / Georges Bresson. |
| Record Nr. | UNINA-9910794157503321 |
| Bingley, England : , : Emerald Publishing, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Essays in honor of Cheng Hsiao / / edited by Tong Li, M. Hashem Pesaran, Dek Terrell
| Essays in honor of Cheng Hsiao / / edited by Tong Li, M. Hashem Pesaran, Dek Terrell |
| Pubbl/distr/stampa | Bingley, England : , : Emerald Publishing, , [2020] |
| Descrizione fisica | 1 online resource (x, 457 pages) : illustrations |
| Disciplina | 330.015195 |
| Collana | Advances in econometrics |
| Soggetto topico | Econometrics |
| ISBN | 1-78973-957-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction / Dek Terrell, Tong Li and M. Hashem Pesaran -- Chapter 1. Correction for the Asymptotical Bias of the Arellano-Bond Type GMM Estimation of Dynamic Panel Models / Yonghui Zhang and Qiankun Zhou -- Chapter 2. Testing Convergence Using HAR Inference / Jianning Kong, Peter C.B. Phillips and Donggyu Sul -- Chapter 3. Model Selection for Explosive Models / Yubo Tao and Jun Yu -- Chapter 4. A VAR Approach to Forecasting Multivariate Long Memory Processes Subject to Structural Breaks / Cindy S.H. Wang and Shui Ki Wan -- Chapter 5. Identifying Global and National Output and Fiscal Policy Shocks Using a GVAR / Alexander Chudik, M Hashem Pesaran and Kamiar Mohaddes -- Chapter 6. The Determinants of Health Care Expenditure and Trends: A Semiparametric Panel Data Analysis of OECD Countries / Ming Kong, Jiti Gao and Xueyan Zhao -- Chapter 7. Growth Empirics: A Bayesian Semiparametric Model with Random Coefficients for a Panel of OECD Countries / Badi H. Baltagi, Georges Bresson and Jean-Michel Etienne -- Chapter 8. Robust Estimation and Inference for Importance Sampling Estimators with Infinite Variance / Joshua C.C. Chan, Chenghan Hou and Thomas Tao Yang -- Chapter 9. Econometrics of Scoring Auctions / Jean-Jacques Laffont, Isabelle Perrigne, Michel Simioni and Quang Vuong -- Chapter 10. Bayesian Estimation of Linear Sum Assignment Problems / Yu-Wei Hsieh and Mathew Shum -- Chapter 11. The Mode ls the Message: Using Predata as Exclusion Restrictions to Evaluate Survey Design / Heng Chen, Geoffrey Dunbar and Q. Rallye Shen -- Chapter 12. Estimating Peer Effects on Career Choice : a Spatial Multinomial Logit Approach / Bolun Li, Robin Sickles and Jenny Williams -- Chapter 13. Mortgage Portfolio Diversification in the Presence of Cross-sectional and Spatial Dependence / Timothy Dombrowski, R. Kelley Pace and Rajesh P. Narayanan -- Chapter 14. An Econometrician's Perspective on Big Data / Cheng Hsiao -- Chapter 15. Comments on "An Econometrician's Perspective on Big Data" by Cheng Hsiao / Thomas B. Fomby -- Chapter 16. Comments on "An Econometrician's Perspective on Big Data" by Cheng Hsiao / Georges Bresson. |
| Record Nr. | UNINA-9910825954203321 |
| Bingley, England : , : Emerald Publishing, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Privacy-Preserving Machine Learning / / by Jin Li, Ping Li, Zheli Liu, Xiaofeng Chen, Tong Li
| Privacy-Preserving Machine Learning / / by Jin Li, Ping Li, Zheli Liu, Xiaofeng Chen, Tong Li |
| Autore | Li Jin |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (VIII, 88 p. 21 illus., 18 illus. in color.) |
| Disciplina |
005.8
323.448 |
| Collana | SpringerBriefs on Cyber Security Systems and Networks |
| Soggetto topico |
Data protection - Law and legislation
Machine learning Privacy Machine Learning Aprenentatge automàtic Seguretat informàtica Protecció de dades |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
9789811691393
9811691398 9789811691386 981169138X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Secure Cooperative Learning in Early Years -- Outsourced Computation for Learning -- Secure Distributed Learning -- Learning with Differential Privacy -- Applications - Privacy-Preserving Image Processing -- Threats in Open Environment -- Conclusion. |
| Record Nr. | UNINA-9910993945703321 |
|
Li Jin
|
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||