دانلود کتاب Secure Edge and Fog Computing Enabled AI for IoT and Smart Cities: Includes selected Papers from International Conference on Advanced Computing & ... Innovations in Communication and Computing)

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Preface
Introduction
Structure of the Book
About This Book
Key Aspects of the Book
Target Audience
References
Contents
About the Editors
Part I AI Enabled Smart City IoT System Using Edge/Fog Computing
Multilevel Edge Computing System for Autonomous Vehicles
1 Introduction
2 V2X Technology Description
3 The Advantage of Edge Computing Technology
4 Model Description
5 Analyze Modeling for the Environment VANET
6 Conclusion
References
UAV-Based Edge Computing System for Smart City Applications
1 Introduction
2 Network Architecture Using MEC/SDN Technologies and UAVs as Edge Nodes
3 Development of a Network Model with Edge and Cloud Computing Nodes
4 Results of the Network Delay Measurement Experiment in the Cloud and Edge Computing Model in High and Low Network Load Scenarios
5 Conclusion
References
Organization of Smart City Services Based on MicroserviceArchitecture
1 Introduction
2 Formulation of the Problem
3 Methodology
3.1 The Architecture of the Developed Service Organization Software
3.2 Service IoTDM
3.3 Smart Device Traffic Generator
3.4 Statistics Service
3.5 The General Architecture of the Developed Software
4 Results and Discussion
4.1 Results of Testing the Developed Model Without Load Distribution Between Microservices
4.2 Results of Testing the Developed Model with Load Distribution Between Microservices
5 Conclusion
References
Pseudo-Random Error-Correcting Codes in Network Coding
1 Introduction
2 Principle of Network Coding
3 Error Control in Network Coding
4 Using Binary Pseudo-Random Codes to Combat Errors in Network Coding
4.1 Maximum Length Code
4.2 Gold Code
4.3 Decoding of MLC and Gold Code
4.4 Network Coding with MLC and Gold Code
5 Conclusion
References
Proactive Management in Smart City: Transport Convoys
1 The Smart City Concept
2 Consistency of Smart City Information Systems
3 System Architecture for Proactive Control of Traffic Columns in Smart City
References
Federated Learning for Linux Malware Detection: An Experimental Study
1 Introduction
2 Related Works
3 Federated Learning Approach for Linux Malware Detection
3.1 Data Collection
3.2 Data Preprocessing
3.3 Training Model
3.4 Model Evaluation
3.5 Server
4 Experiment
4.1 Training Process
4.2 Results
5 Conclusions
References
Delay Prediction in M2M Networks Using the Deep LearningApproach
1 Introduction
2 Literature Review
3 Problem Statement and System Modeling
4 Simulation Results
5 Conclusion
References
Energy-Efficient Beam Shaping in MIMO System Using Machine Learning
1 Introduction
2 Beam-Shaping App
3 Conclusion
References
Channel Cluster Configuration Selection Method for IEEE 802.11 Network Planning
1 Introduction
2 Problem Statement
3 Channel Configuration Selection Method
4 Conclusions
References
Service Migration Algorithm for UAV Recharge Zones in Future 6G Network
1 Introduction
2 Software-Defined Networks
3 Flying Software-Defined Network Architecture
4 Basic Architecture Elements
5 The Main Functions Performed in the UAV Cluster
6 The Proposed Algorithm
7 Conducted Experiment
8 Conclusion
References
FedBA: Non-IID Federated Learning Framework in UAV Networks
1 Introduction
2 Related Works
2.1 Privacy-Preserving UAV Image Recognition
2.2 Federated Learning on Non-IID Data
3 Methodology
3.1 Federated Learning
3.2 Proposed Algorithm
4 Experiment
4.1 Experiment Setup
4.2 Training Details
4.3 Experiment Result
5 Conclusion
References
Part II Fog/Edge Computing Security Issues
Big Data Analytics for Secure Edge-Based Manufacturing Internet of Things (MIoT)
1 Introduction
2 Data Analytics in Manufacturing
3 Data Analytics
4 Data Acquisition
5 Anomaly Detection
6 Data Analytics in MIoT
7 Characteristics of MIoT
8 Comparative Analysis: MIoT vs. CIoT
8.1 Data Acquisition
8.2 Data Processing and Storage
8.3 Data Analytics
9 Necessities of Big Data Analytics
9.1 Improving Processes and Production in Factories
9.2 Reducing Downtime on Computers
9.3 Product Quality Management
9.4 Enhancing Productivity in the Supply Chain
10 Benefits of Big Data Analytics for MIoT
11 Cost Reduction
12 Fraud Detection
13 Product Quality
14 Supply Chain Optimization
15 Demand Forecasting
16 Helps Increase the Businesses\' ROI
17 Advantages to Manufacturing Companies
18 Analysis Depth
19 Security
20 Improving Factory Operations and Production
21 Reducing Machine Downtime
22 Improving Product Quality
23 Enhancing Supply Chain Efficiency
24 Monitoring Manufacturing Process
25 Reduction in Energy Consumption and Energy Costs
26 Reduction of Scrap Rate
27 Challenges of Big Data Analytics for MIoT
28 Easing Security Concerns
29 Overcoming Connectivity Issues
30 Data Acquisition
30.1 Data Representation and Transmission
31 Data Preprocessing and Storage
31.1 Data Integration
31.2 Redundancy Reduction
31.3 Data Cleaning and Data Compression
31.4 Reliability and Persistence of Data Storage
31.5 Scalability
31.6 Efficiency
32 Data Analytics
32.1 Data Temporal and Spatial Correlation
32.2 Efficient Data Mining Schemes
32.3 Privacy and Security
33 Conclusion
References
Artificial Intelligence-Based Secure Edge Computing Systems for IoTDs and Smart Cities: A Survey
1 Introduction
1.1 Chapter Organization
2 Edge Computing
2.1 Security Issues in EC
3 AI Techniques for Securing EC
3.1 Fuzzy Logic-Based Algorithms
3.2 Learning-Based Algorithms
4 AI in Addressing Security Issues in EC
4.1 FLAs for Security and Privacy in EC
4.2 LBAs for Security and Privacy Issues in EC
5 Discussion and Future Research Trends
5.1 Discussion
5.2 Future Research Trends
5.2.1 From EC Perspective
5.2.2 From AI Algorithms Perspective
6 Conclusions
References
Machine Learning Techniques for Secure Edge SDN
1 Introduction
2 Background
2.1 SDN Architecture
2.2 SDN Benefits
3 Security Threats in SDN
4 Machine Learning for Secure SDN
5 Conclusion and Future Directions
References
Machine Learning –Based Identity and Access Management for Cloud Security
1 Introduction
1.1 Motivation
1.2 Comparison
2 Proposed System Architecture
2.1 Clients
2.2 Cloud Service Provider (CSP)
2.3 Multi-cloud Database
2.4 Third-Party Auditor (TPA)
3 Revolutionizing Authentication: A Deep Dive into Federated Identity Transposition
4 Platform for Client Authentication Use of Provisioning in Cloud Computing Structure
5 Results and Discussion
5.1 Dataset Description
5.2 Machine Learning Model Evaluation
5.3 Network Throughput
6 Conclusions, Future Recommendations, and Research Implication
6.1 Future Work
6.2 Implications of the Study
References
Spatial Data of Smart Cities: Trust
1 Spatial Data: Smart City
2 Spatial Data: Confidence Assessment
3 Spatial Data: Ensuring Trust
References
Smart City Infrastructure Projects: Spatial Data of Risks
1 Infrastructure Projects in Smart City
2 Infrastructure Projects Risks in Smart City
References
A Comparative Analysis of Blockchain-Based Authentication Models for IoT Networks
1 Introduction
2 Authentication Methods in IoT Networks
3 Blockchain Concept
3.1 Role of Smart Contract
3.2 Analysis of Blockchain-Based Authentication Models for IoT Networks
4 Conclusions
References
Development of Determining a Wireless Client Location Method in the IEEE 802.11 Network to Ensure the IT Infrastructure Security
1 Introduction
1.1 General Principles of a Wireless Client Positioning in an IEEE 802.11 Network
1.2 Existing Trilateration Methods Based on RSSI
2 Problematics
3 Materials and Methods
4 Results
4.1 Wireless Client Positioning Method
4.2 Placement of Sensors on the Object
4.3 Object\'s Map Creation and Power Map Generation
4.4 Saving Data to a Database
4.5 Client Device Discovery
4.6 Wireless Client Positioning
5 Discussion
5.1 Operation Checking of the Wireless Client Location Method
6 Conclusion
References
Index