E-health applications such as tele-medicine, tele-radiology, tele-ophthalmology, and tele-diagnosis are very promising and have immense potential to improve global healthcare. They can improve access, equity, and quality through the connection of healthcare facilities and healthcare professionals, diminishing geographical and physical barriers. One critical issue, however, is related to the security of data transmission and access to the technologies of medical information. Currently, medical-related identity theft costs billions of dollars each year and altered medical information can put a person’s health at risk through misdiagnosis, delayed treatment or incorrect prescriptions. Yet, the use of hand-held devices for storing, accessing, and transmitting medical information is outpacing the privacy and security protections on those devices. Researchers are starting to develop some imperceptible marks to ensure the tamper-proofing, cost effective, and guaranteed originality of the medical records. However, the robustness, security and efficient image archiving and retrieval of medical data information against these cyberattacks is a challenging area for researchers in the field of e-health applications.
Intelligent Data Security Solutions for e-Health Applications focuses on cutting-edge academic and industry-related research in this field, with particular emphasis on interdisciplinary approaches and novel techniques to provide security solutions for smart applications. The book provides an overview of cutting-edge security techniques and ideas to help graduate students, researchers, as well as IT professionals who want to understand the opportunities and challenges of using emerging techniques and algorithms for designing and developing more secure systems and methods for e-health applications.
1. Cover image - p. page_i 2. Title page - p. page_i 3. Table of Contents - p. page_i 4. Copyright - p. page_iv 5. Contributors - p. page_xv 6. Preface - p. page_xix 7. Chapter 1: Perceptual hashing-based novel security framework for medical images - p. page_1 8. Chapter 2: Frequency domain based data hiding for encrypted medical images - p. page_21 9. Chapter 3: An OpenSim guided tour in machine learning for e-health applications - p. page_57 10. Chapter 4: Advances and challenges in fMRI and DTI techniques - p. page_77 11. Chapter 5: Homomorphic transform-based dual image watermarking using IWT-SVD for secure e-healthcare applications - p. page_91 12. Chapter 6: An analysis of security access control on healthcare records in the cloud - p. page_113 13. Chapter 7: Security and interference management in the cognitive-inspired Internet of Medical Things - p. page_131 14. Chapter 8: Access control and classifier-based blockchain technology in e-healthcare applications - p. page_151 15. Chapter 9: Machine learning algorithms for medical image security - p. page_169 16. Chapter 10: Genetic algorithm-based intelligent watermarking for security of medical images in telemedicine applications - p. page_185 17. Chapter 11: Data security for WBAN in e-health IoT applications - p. page_205 18. Chapter 12: Cloud-based computer-assisted diagnostic solutions for e-health - p. page_219 19. Chapter 13: Progressive advancements in security challenges, issues, and solutions in e-health systems - p. page_237 20. Chapter 14: Despeckling of ultrasound images based on the multiresolution approach and Gaussianization transform - p. page_255 21. Chapter 15: Wireless medical sensor networks for smart e-healthcare - p. page_275 22. Chapter 16: A secure lightweight mutual authentication and key agreement protocol for healthcare systems - p. page_293 23. Index - p. page_309
E-health applications such as tele-medicine, tele-radiology, tele-ophthalmology, and tele-diagnosis are very promising and have immense potential to improve global healthcare. They can improve access, equity, and quality through the connection of healthcare facilities and healthcare professionals, diminishing geographical and physical barriers. One critical issue, however, is related to the security of data transmission and access to the technologies of medical information. Currently, medical-related identity theft costs billions of dollars each year and altered medical information can put a person’s health at risk through misdiagnosis, delayed treatment or incorrect prescriptions. Yet, the use of hand-held devices for storing, accessing, and transmitting medical information is outpacing the privacy and security protections on those devices. Researchers are starting to develop some imperceptible marks to ensure the tamper-proofing, cost effective, and guaranteed originality of the medical records. However, the robustness, security and efficient image archiving and retrieval of medical data information against these cyberattacks is a challenging area for researchers in the field of e-health applications.
Intelligent Data Security Solutions for e-Health Applications focuses on cutting-edge academic and industry-related research in this field, with particular emphasis on interdisciplinary approaches and novel techniques to provide security solutions for smart applications. The book provides an overview of cutting-edge security techniques and ideas to help graduate students, researchers, as well as IT professionals who want to understand the opportunities and challenges of using emerging techniques and algorithms for designing and developing more secure systems and methods for e-health applications.
1. Cover image - p. page_i 2. Title page - p. page_i 3. Table of Contents - p. page_i 4. Copyright - p. page_iv 5. Contributors - p. page_xv 6. Preface - p. page_xix 7. Chapter 1: Perceptual hashing-based novel security framework for medical images - p. page_1 8. Chapter 2: Frequency domain based data hiding for encrypted medical images - p. page_21 9. Chapter 3: An OpenSim guided tour in machine learning for e-health applications - p. page_57 10. Chapter 4: Advances and challenges in fMRI and DTI techniques - p. page_77 11. Chapter 5: Homomorphic transform-based dual image watermarking using IWT-SVD for secure e-healthcare applications - p. page_91 12. Chapter 6: An analysis of security access control on healthcare records in the cloud - p. page_113 13. Chapter 7: Security and interference management in the cognitive-inspired Internet of Medical Things - p. page_131 14. Chapter 8: Access control and classifier-based blockchain technology in e-healthcare applications - p. page_151 15. Chapter 9: Machine learning algorithms for medical image security - p. page_169 16. Chapter 10: Genetic algorithm-based intelligent watermarking for security of medical images in telemedicine applications - p. page_185 17. Chapter 11: Data security for WBAN in e-health IoT applications - p. page_205 18. Chapter 12: Cloud-based computer-assisted diagnostic solutions for e-health - p. page_219 19. Chapter 13: Progressive advancements in security challenges, issues, and solutions in e-health systems - p. page_237 20. Chapter 14: Despeckling of ultrasound images based on the multiresolution approach and Gaussianization transform - p. page_255 21. Chapter 15: Wireless medical sensor networks for smart e-healthcare - p. page_275 22. Chapter 16: A secure lightweight mutual authentication and key agreement protocol for healthcare systems - p. page_293 23. Index - p. page_309
