AI-Driven Cybersecurity for Intelligent Healthcare Systems explores the intersection between AI, cybersecurity, and healthcare. The book offers detailed insights into the unique cybersecurity challenges faced by the healthcare sector and the role of AI in addressing these challenges. It presents case studies and real-world applications to illustrate the effectiveness of these solutions and highlights the significance of data privacy in healthcare and methods to ensure secure data sharing and storage. Topics such as federated learning, homomorphic encryption, and blockchain technology are covered to demonstrate how AI can enhance data security without compromising patient privacy.
This book will be an essential resource for anyone involved in the healthcare industry, offering practical solutions and fostering a more in-depth understanding of how AI can revolutionize cybersecurity in healthcare.
1. Title of Book - p. i 2. Cover Image - p. i 3. Title Page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. Contributors - p. xi 7. Chapter 1 Smart healthcare systems with improved cybersecurity by AI integration - p. 1 8. Chapter 2 Transforming healthcare Harnessing the power of AI in the modern era - p. 21 9. Chapter 3 Machine learning-enhanced threat intelligence for advanced cybersecurity - p. 35 10. Chapter 4 Progress and prospects of blockchain for healthcare - p. 51 11. Chapter 5 Using AI to improve the security of the Internet of Medical Things: A thorough analysis - p. 69 12. Chapter 6 Enhancing cybersecurity strategies for multicloud healthcare systems through deep learning-based threat detection and mitigation - p. 91 13. Chapter 7 Intelligent access control mechanisms in cybersecurity: A technique for health data security - p. 115 14. Chapter 8 AI-driven threat detection and response: A paradigm shift in cybersecurity - p. 135 15. Chapter 9 Blockchain for healthcare to secure patient data and enabling trusted artificial “intelligence” - p. 151 16. Chapter 10 Deep learning techniques for securing data in healthcare applications - p. 167 17. Chapter 11 Chat bot systems in healthcare: AI integration and security measures - p. 187 18. Chapter 12 A comprehensive survey of smart medical wearables in fitness and health monitoring - p. 211 19. Chapter 13 Recent advancements in emerging technologies for secure healthcare management systems - p. 237 20. Chapter 14 AI-driven risk assessment models for predicting healthcare cybersecurity threats in real-time - p. 257 21. Chapter 15 Responsible AI in healthcare: Navigating ethics and governance challenges - p. 291 22. Index - p. 321
AI-Driven Cybersecurity for Intelligent Healthcare Systems explores the intersection between AI, cybersecurity, and healthcare. The book offers detailed insights into the unique cybersecurity challenges faced by the healthcare sector and the role of AI in addressing these challenges. It presents case studies and real-world applications to illustrate the effectiveness of these solutions and highlights the significance of data privacy in healthcare and methods to ensure secure data sharing and storage. Topics such as federated learning, homomorphic encryption, and blockchain technology are covered to demonstrate how AI can enhance data security without compromising patient privacy.
This book will be an essential resource for anyone involved in the healthcare industry, offering practical solutions and fostering a more in-depth understanding of how AI can revolutionize cybersecurity in healthcare.
1. Title of Book - p. i 2. Cover Image - p. i 3. Title Page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. Contributors - p. xi 7. Chapter 1 Smart healthcare systems with improved cybersecurity by AI integration - p. 1 8. Chapter 2 Transforming healthcare Harnessing the power of AI in the modern era - p. 21 9. Chapter 3 Machine learning-enhanced threat intelligence for advanced cybersecurity - p. 35 10. Chapter 4 Progress and prospects of blockchain for healthcare - p. 51 11. Chapter 5 Using AI to improve the security of the Internet of Medical Things: A thorough analysis - p. 69 12. Chapter 6 Enhancing cybersecurity strategies for multicloud healthcare systems through deep learning-based threat detection and mitigation - p. 91 13. Chapter 7 Intelligent access control mechanisms in cybersecurity: A technique for health data security - p. 115 14. Chapter 8 AI-driven threat detection and response: A paradigm shift in cybersecurity - p. 135 15. Chapter 9 Blockchain for healthcare to secure patient data and enabling trusted artificial “intelligence” - p. 151 16. Chapter 10 Deep learning techniques for securing data in healthcare applications - p. 167 17. Chapter 11 Chat bot systems in healthcare: AI integration and security measures - p. 187 18. Chapter 12 A comprehensive survey of smart medical wearables in fitness and health monitoring - p. 211 19. Chapter 13 Recent advancements in emerging technologies for secure healthcare management systems - p. 237 20. Chapter 14 AI-driven risk assessment models for predicting healthcare cybersecurity threats in real-time - p. 257 21. Chapter 15 Responsible AI in healthcare: Navigating ethics and governance challenges - p. 291 22. Index - p. 321
