The management and control of networks can no longer be envisaged without the introduction of artificial intelligence at all stages. Intelligent Network Management and Control deals with topical issues related mainly to intelligent security of computer networks, deployment of security services in SDN (software-defined networking), optimization of networks using artificial intelligence techniques and multi-criteria optimization methods for selecting networks in a heterogeneous environment. This book also focuses on selecting cloud computing services, intelligent unloading of calculations…mehr
The management and control of networks can no longer be envisaged without the introduction of artificial intelligence at all stages.
Intelligent Network Management and Control deals with topical issues related mainly to intelligent security of computer networks, deployment of security services in SDN (software-defined networking), optimization of networks using artificial intelligence techniques and multi-criteria optimization methods for selecting networks in a heterogeneous environment.
This book also focuses on selecting cloud computing services, intelligent unloading of calculations in the context of mobile cloud computing, intelligent resource management in a smart grid-cloud system for better energy efficiency, new architectures for the Internet of Vehicles (IoV), the application of artificial intelligence in cognitive radio networks and intelligent radio input to meet the on-road communication needs of autonomous vehicles.
Badr Benmammar is currently a Professor in the Computer Science department at the Abou Bakr Belkaïd University of Tlemcen, Algeria, having received his PhD in Computer Science from Bordeaux 1 University, France. He is the author of several books, including Radio Resource Allocation and Dynamic Spectrum Access (ISTE-Wiley), and his work has led to many journal publications.
Inhaltsangabe
Introduction xiii Badr BENMAMMAR
Part 1. AI and Network Security 1
Chapter 1. Intelligent Security of Computer Networks 3 Abderrazaq SEMMOUD and Badr BENMAMMAR
1.1. Introduction 3
1.2. AI in the service of cybersecurity 5
1.3. AI applied to intrusion detection 8
1.3.1. Techniques based on decision trees 9
1.3.2. Techniques based on data exploration 9
1.3.3. Rule-based techniques 10
1.3.4. Machine learning-based techniques 11
1.3.5. Clustering techniques 13
1.3.6. Hybrid techniques 14
1.4. AI misuse 15
1.4.1. Extension of existing threats 16
1.4.2. Introduction of new threats 16
1.4.3. Modification of the typical threat character 17
1.5. Conclusion 17
1.6. References 18
Chapter 2. An Intelligent Control Plane for Security Services Deployment in SDN-based Networks 25 Maïssa MBAYE, Omessaad HAMDI and Francine KRIEF
2.1. Introduction 25
2.2. Software-defined networking 27
2.2.1. General architecture 27
2.2.2. Logical distribution of SDN control 29
2.3. Security in SDN-based networks 32
2.3.1. Attack surfaces 33
2.3.2. Example of security services deployment in SDN-based networks: IPSec service 34
2.4. Intelligence in SDN-based networks 40
2.4.1. Knowledge plane 41
2.4.2. Knowledge-defined networking 41
2.4.3. Intelligence-defined networks 42
2.5. AI contribution to security 43
2.5.1. ML techniques 43
2.5.2. Contribution of AI to security service: intrusion detection 47
2.6. AI contribution to security in SDN-based networks 48
2.7. Deployment of an intrusion prevention service 49
2.7.1. Attack signature learning as cloud service 50
2.7.2. Deployment of an intrusion prevention service in SDN-based networks 52
2.8. Stakes 55
2.9. Conclusion 56
2.10. References 56
Part 2. AI and Network Optimization 63
Chapter 3. Network Optimization using Artificial Intelligence Techniques 65 Asma AMRAOUI and Badr BENMAMMAR
3.1. Introduction 65
3.2. Artificial intelligence 66
3.2.1. Definition 66
3.2.2. AI techniques 67
3.3. Network optimization 73
3.3.1. AI and optimization of network performances 73
3.3.2. AI and QoS optimization 74
3.3.3. AI and security 75
3.3.4. AI and energy consumption 77
3.4. Network application of AI 77
3.4.1. ESs and networks 77
3.4.2. CBR and telecommunications networks 79
3.4.3. Automated learning and telecommunications networks 79
3.4.4. Big data and telecommunications networks 80
3.4.5. MASs and telecommunications networks 82
3.4.6. IoT and networks 84
3.5. Conclusion 85
3.6. References 85
Chapter 4. Multicriteria Optimization Methods for Network Selection in a Heterogeneous Environment 89 Fayssal BENDAOUD
4.1. Introduction 89
4.2. Multicriteria optimization and network selection 91
4.2.1. Network selection process 92
4.2.2. Multicriteria optimization methods for network selection 94
4.3. "Modified-SAW" for network selection in a heterogeneous environment 99
4.3.1. "Modified-SAW" proposed method 100
4.3.2. Performance evaluation 104
4.4. Conclusion 113
4.5. References 113
Part 3. AI and the Cloud Approach 117
Chapter 5. Selection of Cloud Computing Services: Contribution of Intelligent Methods 119
