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Full Description
Modern enterprises are facing growing cybersecurity issues due to the massive volume of security-related data they generate over time. AI systems can be developed to resolve a range of these issues with comparative ease. This new book describes the various types of cybersecurity problems faced by businesses and how advanced AI algorithms and models can help eliminate them.
With chapters from industry and security experts, this volume discribes the various types of cybersecurity problems faced by businesses and how advanced AI algorithms and models can help elimintate them. With chapters from industry and security experts, this volume discusses the many new and emerging AI technologies and approaches that can be harnessed to combat cyberattacks, including big data analytics techniques, deep neural networks, cloud computer networks, convolutional neural networks, IoT edge devices, machine learning approaches, deep learning, blockchain technology, convolutional neural networks, and more.
Some unique features of this book include:
Detailed overview of various security analytics techniques and tools
Comprehensive descriptions of the emerging and evolving aspects of artificial intelligence (AI) technologies
Industry case studies for practical comprehension and application
This book, Leveraging the Artificial Intelligence Competencies for Next-Generation Cybersecurity Solutions, illustrates how AI is a futuristic and flexible technology that can be effectively used for tackling the growing menace of cybercriminals. It clearly demystifies the unique contributions of AI algorithms, models, frameworks, and libraries in nullifying the cyberattacks. The volume will be a valuable resource for research students, scholars, academic professors, business executives, security architects, and consultants in the IT industry.
Contents
1. Network Security Risks and Solutions Through Automated Toolkits in Underwater Sensor Networks: Survey 2. IoT Security: Challenges, Best Practices, and Service Platforms 3. A Fundamental Overview in Cybersecurity: Prevention and Mitigation of Cyberattacks for Securing Cyberspace 4. A Review of Big Data Analytics Techniques to Collar Cybersecurity Concerns 5. Deep Neural Networks for Automated Cyber Security: Identification of Dynamic Malware in Cloud Computer Networks 6. Artificial Intelligence Models for Cyber Security 7. Demystifying Digital Transformation Technologies and Tools 8. Big Data Analytics in Cyber Threats and Artificial Intelligence 9. Cyber Security-Based Solutions for IoT Edge Devices: Critical Issues and Services 10. A Structural Framework for Modeling Multi-Stage Network Attacks 11. Artificial Intelligence Techniques for Malicious Domain Detection in Cyberspace 12. Malicious Domains Detection Based on Machine Learning Techniques 13. Use of Artificial Intelligence and the Thread Detection Method in Cyber Security 14. The Impact of AI on Cybersecurity in Sustainable Universal Health Care: Current Developments, Issues, and Future Prospects 15. Delineating the Critical Cloud Infrastructure, Application, and Data for Business Agility and Reliability 16. Machine Learning Approaches for Dynamic Cyber Security 17. Cyber Security in Deep Learning: Challenges and Applications 18. Revolution of Digital Transformation Technology: Artificial Intelligence and Blockchain Technology in Cyber Security 19. A Survey of Deep Learning Algorithms and Methods for Automated Cyber Security in Healthcare 20. An Intrusion Detection System Using the NSL-KDD Dataset's Convolutional Neural Network and Data Analytics 21. Cyber Security Through Big Data Analytics
