NGC-2023: Next-Generation Cybersecurity - AI, ML, and Blockchain |
Website | https://www.springernature.com/gp |
Submission link | https://easychair.org/conferences/?conf=ngc2023 |
Abstract registration deadline | April 30, 2023 |
Submission deadline | May 31, 2023 |
Title of the Book: Next-Generation Cybersecurity with AI, ML, and Blockchain.
This book highlights a comprehensive overview of the recent advancements and challenges in the field of cybersecurity with a focus on the integration of Artificial Intelligence (AI), Machine Learning (ML), and Blockchain technologies. The book targets both researchers and practitioners working in the field of cybersecurity and aims to fill the gap in the current literature by providing a comprehensive and up-to-date examination of the integration of AI, ML, and blockchain in cybersecurity systems.The book has a technical focus and provides an in-depth examination of the latest developments in the field. It covers a range of topics including the basics of AI, ML, and blockchain, the application of AI and ML in cybersecurity, the use of blockchain in cybersecurity, and the integration of AI, ML, and blockchain in cybersecurity systems. Each chapter is written by leading experts in the field and provides a thorough and technical overview of the topic, including case studies, examples, and practical applications.
Submission Guidelines
All book chapters must be original and not simultaneously submitted to another journal or conference. The book chapter should have a minimum of 20 pages, plagiarism below 10% and high quality images.
List of Topics
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Table of contents (but are not limited to):
Chapter 1: Introduction to Cybersecurity with AI, ML and Blockchain
• Overview of the evolution of cybersecurity
• The impact of AI, ML and blockchain on cybersecurity
• The importance of interdisciplinary approaches to tackle cybersecurity challenges
Chapter 2: AI and ML for Threat Detection and Mitigation
• Overview of AI and ML in cybersecurity
• Threat detection and mitigation using AI and ML
• Approaches for feature extraction and classification in AI-based threat detection
Chapter 3: AI and ML for Network Security
• Overview of network security and its challenges
• AI and ML-based network security solutions
• Applications of AI and ML in network intrusion detection and prevention
Chapter 4: Enhancing Cybersecurity with Reinforcement Learning
• Overview of reinforcement learning in cybersecurity
• Applications of reinforcement learning in cybersecurity
• Comparison of reinforcement learning with other AI-based approaches in cybersecurity
Chapter 5: Blockchain for Secure Data Management
• Overview of blockchain technology and its characteristics
• Blockchain-based secure data management systems
• Applications of blockchain in secure data storage and sharing
Chapter 6: Decentralized Security Solutions with Blockchain
• Overview of decentralized security solutions
• Blockchain-based decentralized security solutions
• Applications of blockchain in decentralized security systems
Chapter 7: Blockchain-based Cyber Threat Intelligence Sharing
• Overview of cyber threat intelligence and its importance
• Blockchain-based cyber threat intelligence sharing systems
• Advantages of blockchain-based cyber threat intelligence sharing
Chapter 8: Ethical Considerations in AI-based Cybersecurity
• Overview of ethical considerations in AI-based cybersecurity
• Privacy and security concerns with AI-based cybersecurity
• Responsibility and accountability of AI-based cybersecurity systems
Chapter 9: Ethical Considerations in Blockchain-based Cybersecurity
• Overview of ethical considerations in blockchain-based cybersecurity
• Privacy and security concerns with blockchain-based cybersecurity
• Responsibility and accountability of blockchain-based cybersecurity systems
Chapter 10: Cybersecurity with AI and Blockchain in Healthcare
• Overview of healthcare cybersecurity and its challenges
• AI and blockchain-based solutions for healthcare cybersecurity
• Case studies of AI and blockchain-based healthcare cybersecurity systems
Chapter 11: Cybersecurity with AI and Blockchain in Finance
• Overview of finance cybersecurity and its challenges
• AI and blockchain-based solutions for finance cybersecurity
• Case studies of AI and blockchain-based finance cybersecurity systems
Chapter 12: Cybersecurity with AI and Blockchain in IoT
• Overview of IoT cybersecurity and its challenges
• AI and blockchain-based solutions for IoT cybersecurity
• Case studies of AI and blockchain-based IoT cybersecurity systems
Chapter 13: Cybersecurity with AI and Blockchain in Cloud Computing
• Overview of cloud computing cybersecurity and its challenges
• AI and blockchain-based solutions for cloud computing cybersecurity
• Case studies of AI and blockchain-based cloud computing cybersecurity systems
Chapter 14: AI and Blockchain for Secure Data Analytics
• Overview of secure data analytics and its challenges
• AI and blockchain-based solutions for secure data analytics
• Case studies of AI and blockchain-based secure data analytics systems
Chapter 15: AI and Blockchain for Secure Identity Management
• Overview of secure identity management and its challenges
• AI and blockchain-based solutions for secure identity management
• Case studies of AI and blockchain-based secure identity management systems
Chapter 16: AI and Blockchain for Secure Communication
• Overview of secure communication and its challenges
• AI and blockchain-based solutions for secure communication
• Case studies of AI and blockchain-based secure communication systems
Chapter 17: AI and Blockchain for Secure Supply Chain Management
• Overview of supply chain management and its security challenges
• AI and blockchain-based solutions for secure supply chain management
• Case studies of AI and blockchain-based secure supply chain management systems
• Discussion of the benefits of integrating AI and blockchain in supply chain management and the challenges that still need to be addressed.
Chapter 18: Integration of AI, ML, and Blockchain in Cybersecurity
• Overview of the integration of AI, ML, and blockchain in cybersecurity
• Approaches for integrating AI, ML, and blockchain in cybersecurity systems
• Case studies of AI, ML, and blockchain-integrated cybersecurity systems
Chapter 19: Impact of Neural Networks for Malware Detection
• Overview of Artificial Neural Network
• How ANNs are suitable for Malware Detection
• Performance comparison of ANN based solutions with ML based solutions
Chapter 20: Future Directions in Cybersecurity with AI, ML, and Blockchain
• Overview of the current trends and future directions in cybersecurity with AI, ML, and blockchain
• Research challenges and opportunities in the field
• Discussion of the potential impact of AI, ML, and blockchain on the future of cybersecurity
Publication
NGC-2023 proceedings will be published in Springer under Book Series Blockchain Technologies
Contact
All questions about submissions should be emailed to ishu.sharma001@gmail.com, officialkeshavkaushik@gmail.com