Autonomous Vehicles, Volume 1

Table of contents

1. Cover
2. Series Page
3. Title Page
4. Copyright Page
5. Preface
6. 1 Anomalous Activity Detection Using Deep Learning Techniques in Autonomous Vehicles
   1. 1.1 Introduction
   2. 1.2 Literature Review
   3. 1.3 Artificial Intelligence in Autonomous Vehicles
   4. 1.4 Technologies Inside Autonomous Vehicle
   5. 1.5 Major Tasks in Autonomous Vehicle Using AI
   6. 1.6 Benefits of Autonomous Vehicle
   7. 1.7 Applications of Autonomous Vehicle
   8. 1.8 Anomalous Activities and Their Categorization
   9. 1.9 Deep Learning Methods in Autonomous Vehicle
   10. 1.10 Working of Yolo
   11. 1.11 Proposed Methodology
   12. 1.12 Proposed Algorithms
   13. 1.13 Comparative Study and Discussion
   14. 1.14 Conclusion
   15. References
7. 2 Algorithms and Difficulties for Autonomous Cars Based on Artificial Intelligence
   1. 2.1 Introduction
   2. 2.2 In Autonomous Cars, AI Algorithms are Applied
   3. 2.3 AI’s Challenges with Self-Driving Vehicles
   4. 2.4 Conclusion
   5. References
8. 3 Trusted Multipath Routing for Internet of Vehicles against DDoS Assault Using Brink Controller in Road Awareness (TMRBC-IOV)
   1. 3.1 Introduction
   2. 3.2 Related Work
   3. 3.3 VANET Grouping Algorithm (VGA)
   4. 3.4 Extension of Trusted Multipath Distance Vector Routing (TMDR-Ext)
   5. 3.5 Conclusion
   6. References
9. 4 Technological Transformation of Middleware and Heuristic Approaches for Intelligent Transport System
   1. 4.1 Introduction
   2. 4.2 Evolution of VANET
   3. 4.3 Middleware Approach
   4. 4.4 Heuristic Search
   5. 4.5 Reviews of Middleware Approaches
   6. 4.6 Reviews of Heuristic Approaches
   7. 4.7 Conclusion and Future Scope
   8. References
10. 5 Recent Advancements and Research Challenges in Design and Implementation of Autonomous Vehicles
    1. 5.1 Introduction
    2. 5.2 Modules/Major Components of Autonomous Vehicles
    3. 5.3 Testing and Analysis of An Autonomous Vehicle in a Virtual Prototyping Environment
    4. 5.4 Application Areas of Autonomous Vehicles
    5. 5.5 Artificial Intelligence (AI) Approaches for Autonomous Vehicles
    6. 5.6 Challenges to Design Autonomous Vehicles
    7. 5.7 Conclusion
    8. References
11. 6 Review on Security Vulnerabilities and Defense Mechanism in Drone Technology
    1. 6.1 Introduction
    2. 6.2 Background
    3. 6.3 Security Threats in Drones
    4. 6.4 Defense Mechanism and Countermeasure Against Attacks
    5. 6.5 Conclusion
    6. References
12. 7 Review of IoT-Based Smart City and Smart Homes Security Standards in Smart Cities and Home Automation
    1. 7.1 Introduction
    2. 7.2 Overview and Motivation
    3. 7.3 Existing Research Work
    4. 7.4 Different Security Threats Identified in IoT-Used Smart Cities and Smart Homes
    5. 7.5 Security Solutions For IoT-Based Environment in Smart Cities and Smart Homes
    6. 7.6 Conclusion
    7. References
13. 8 Traffic Management for Smart City Using Deep Learning
    1. 8.1 Introduction
    2. 8.2 Literature Review
    3. 8.3 Proposed Method
    4. 8.4 Experimental Evaluation
    5. 8.5 Conclusion
    6. References
14. 9 Cyber Security and Threat Analysis in Autonomous Vehicles
    1. 9.1 Introduction
    2. 9.2 Autonomous Vehicles
    3. 9.3 Related Works
    4. 9.4 Security Problems in Autonomous Vehicles
    5. 9.5 Possible Attacks in Autonomous Vehicles
    6. 9.6 Defence Strategies against Autonomous Vehicle Attacks
    7. 9.7 Cyber Threat Analysis
    8. 9.8 Security and Safety Standards in AVs
    9. 9.9 Conclusion
    10. References
15. 10 Big Data Technologies in UAV’s Traffic Management System: Importance, Benefits, Challenges and Applications
    1. 10.1 Introduction
    2. 10.2 Literature Review
    3. 10.3 Overview of UAV’s Traffic Management System
    4. 10.4 Importance of Big Data Technologies and Algorithm
    5. 10.5 Benefits of Big Data Techniques in UTM
    6. 10.6 Challenges of Big Data Techniques in UTM
    7. 10.7 Applications of Big Data Techniques in UTM
    8. 10.8 Case Study and Future Aspects
    9. 10.9 Conclusion
    10. References
16. 11 Reliable Machine Learning-Based Detection for Cyber Security Attacks on Connected and Autonomous Vehicles
    1. 11.1 Introduction
    2. 11.2 Literature Survey
    3. 11.3 Proposed Architecture
    4. 11.4 Experimental Results
    5. 11.5 Analysis of the Proposal
    6. 11.6 Conclusion
    7. References
17. 12 Multitask Learning for Security and Privacy in IoV (Internet of Vehicles)
    1. 12.1 Introduction
    2. 12.2 IoT Architecture [5]
    3. 12.3 Taxonomy of Various Security Attacks in Internet of Things [5]
    4. 12.4 Machine Learning Algorithms for Security and Privacy in IoV
    5. 12.5 A Machine Learning-Based Learning Analytics Methodology for Security and Privacy in Internet of Vehicles
    6. 12.6 Conclusion
    7. References
18. 13 ML Techniques for Attack and Anomaly Detection in Internet of Things Networks
    1. 13.1 Introduction
    2. 13.2 Internet of Things
    3. 13.3 Cyber-Attack in IoT
    4. 13.4 IoT Attack Detection in ML Technics
    5. 13.5 Conclusion
    6. References
19. 14 Applying Nature-Inspired Algorithms for Threat Modeling in Autonomous Vehicles
    1. 14.1 Introduction
    2. 14.2 Related Work
    3. 14.3 Proposed Mechanism
    4. 14.4 Performance Results
    5. 14.5 Future Directions
    6. 14.6 Conclusion
    7. References
20. 15 The Smart City Based on AI and Infrastructure: A New Mobility Concepts and Realities
    1. 15.1 Introduction
    2. 15.2 Research Method
    3. 15.3 Vehicles that are Both Networked and Autonomous
    4. 15.4 Personal Aerial Automobile Vehicles and Unmanned Aerial Automobile Vehicles
    5. 15.5 Mobile Connectivity as a Service
    6. 15.6 Major Role for Smart City Development with IoT and Industry 4.0
    7. 15.7 Conclusion
    8. References
21. Index
22. End User License Agreement