Securing Health (eBook, PDF)

The Convergence of AI and Cybersecurity in Healthcare
Redaktion: Sulaiman, Rejwan Bin; Nipun, Musarrat Saberin; Talukder, Md. Simul Hasan; Aljaidi, Mohammad; Maleh, Yassine; Butt, Usman Javed

• Format: PDF

Produktbeschreibung

Securing Health: The Convergence of AI and Cybersecurity in Healthcare explores how emerging technologies are revolutionizing modern medicine, ensuring not just innovation but safety and trust in the digital age. As artificial intelligence and cybersecurity rapidly transform industries, this timely book offers an in-depth look at their powerful convergence within the healthcare sector.

Organized into four comprehensive parts, the book unveils cutting-edge strategies and practical applications shaping the future of medicine. From blockchain integration and smart wearables to adversarial machine learning and federated learning, each chapter offers critical insights into securing sensitive data, enhancing diagnostic accuracy, and preserving patient privacy.

Discover how blockchain is being used to protect medical records and power real-time health monitoring for athletes, with a special focus on deployments in regions like Kurdistan. Learn how AI-driven tools are predicting complex diseases like cerebral palsy and post-transplant diabetes, offering hope for earlier intervention and better outcomes. Dive into the world of deep learning as it redefines medical imaging, from detecting COVID-19 via X-rays to advancing brain MRI segmentation.

With contributions grounded in global case studies and research, Securing Health addresses the ethical, technical, and regulatory challenges of modern healthcare technology. Whether you're a medical professional, tech innovator, or policy maker, this book equips you with the knowledge to navigate and lead in an era where AI and cybersecurity aren't just enhancements-they're essentials.

Empowering, forward-thinking, and solution-focused, Securing Health is your essential guide to the future of secure, intelligent healthcare.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 386
• Erscheinungstermin: 8. Dezember 2025
• Englisch
• ISBN-13: 9781040448540
• Artikelnr.: 75696407

Autorenporträt

Rejwan Bin Sulaiman, PhD, is a cybersecurity expert, researcher, and lecturer specializing in Artificial Intelligence (AI), and Cybersecurity. He holds a PhD in AI and Cybersecurity from the University of Bedfordshire, along with a BSc (Hons) and an MSc in Computer Science. With extensive academic and industry experience, he has served as a lecturer at institutions such as Northumbria University, the University of Law, and the University of Bedfordshire. Rejwan's research focuses on cybersecurity, medical image processing, and financial fraud detection. He has authored numerous peer-reviewed publications in high-impact journals and presented his work at international conferences. His achievements include securing research grants, receiving the student-led Teaching Award, and leading an Innovate UK-funded project on AI-driven sales optimization. Beyond academia, Rejwan is the founder of STEMResearch.Ai, where he leads a team of researchers in publishing cutting-edge research on AI and machine learning. He holds professional certifications, including AWS Solution Architect Associate, Google Data Analytics, and EC-Council Certified Ethical Hacker (C EH). Rejwan is deeply committed to fostering innovation in teaching and research, mentoring students, and advancing knowledge in cybersecurity and AI. Additionally, Rejwan actively participates as a reviewer and serves as a member of the Technical Program Committee at different IEEE conferences. His professional affiliations with IEEE and BCS provide him with opportunities to engage with a wide range of seminars and research workshops, enabling him to stay up to date with the latest advancements in his field. Usman Javed Butt received the PhD degree in cybersecurity from Brunel University in 2023, MSc. Degree in Computer Networks and Systems Security from the University of Greenwich, UK in 2010 and Bachelor of Computer Science (Hons) degree in 2003. He is currently an Assistant Professor of cybersecurity with the Department of Engineering and Information Technology, Ajman University, UAE. He is a Fellow of the Higher Education Academy (FHEA). He is a certified Ethical Hacker, Certified CISMP and Certified ISO27001 Practitioner. He is also trained in NCSC, UK CyberFirst initiative. Along with his academic experience, he also possesses commercial experience and has worked as a Systems Administrator and Network Engineer. He has authored several papers in journals, conferences and chapters in edited books. His current research interests include Cyber-Physical Systems, Game-based learning in cybersecurity, Cyber Resilience, Threat Intelligence, Responsible AI and the Role of AI in Cybersecurity. Yassine Maleh is an associate professor of cybersecurity and IT governance at Sultan Moulay Slimane University, Morocco, since 2019. He is the founding chair of IEEE Consultant Network Morocco and founding president of the African Research Center of Information Technology & Cybersecurity. He is a former CISO at the National Port Agency between 2012-2019. He is a senior member of IEEE and a member of the International Association of Engineers IAENG and The Machine Intelligence Research Labs. Dr Maleh has made contributions in the fields of information security and privacy, Internet of things security, wireless and constrained networks security. His research interests include information security and privacy, Internet of things, networks security, information system, and IT governance. He has published over 200 papers (book chapters, international journals, and conferences/workshops), 40 edited books, and 8 authored books. He is the editor-in-chief of the International Journal of Information Security and Privacy (IJISP, IF: 0.8), and the International Journal of Smart Security Technologies (IJSST). He serves as an associate editor for IEEE Access, since 2019 (Impact Factor 4.098), the International Journal of Digital Crime and Forensics (IJDCF), and the International Journal of Information Security and Privacy (IJISP). He is a series editor of Advances in Cybersecurity Management, by CRC Taylor & Francis. He was also a guest editor for many special issues with prestigious journals (ieee transactions on industrial informatics, EEE Engineering Management Review, Sensors, Big Data Journal). He has served and continues to serve on executive and technical program committees and as a reviewer of numerous international conferences and journals such as Elsevier Ad Hoc Networks, IEEE Network Magazine, IEEE Sensor Journal, ICT Express, and Springer Cluster Computing. He was the General chair and publication chair of many international conferences (BCCA 2019, MLBDACP 19, ICI2C'21, ICACNGC 2022, CCSET'22, IEEE ISC2 2022, ISGTA'24, etc...). He received Publons Top 1% reviewer award for the years 2018 and 2019. Mohammad Aljaidi received his B.Sc. (Honours with Distinction) in Computer Science from Zarqa University, Jordan, in 2014; the M.Sc. (Honours with Distinction) in Computer Science from Zarqa University, Jordan, in 2017; and the Ph.D. degree in Computer Science and Artificial Intelligence from the University of Northumbria at Newcastle, UK, in 2022. Dr. Aljaidi is currently working as an Assistant Professor with the Computer Science Department, Zarqa University, Jordan. His research interests include but are not limited to, EVs charging management and development, wireless sensor networks (WSNs), AI, Cyber security, optimization, IoT, and reinforcement learning. He has published more than 100 research papers and granted them with 9 patents. He has served as a reviewer of numerous international conferences and journals such as IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Intelligent Vehicles, IEEE Transactions on Instrumentation and Measurement, IEEE Access, and many other journals in Springer and ScienceDirect (Elsevier) Md. Simul Hasan Talukder is a dedicated academician and researcher specializing in Image Processing, Machine Learning, and Deep Learning. Currently serving as a Lecturer at Dhaka University of Engineering and Technology (DUET), Gazipur, he has also worked at esteemed institutions like Bangladesh Atomic Energy Regulatory Authority, Bangladesh Army University of Engineering and Technology. He holds a B.Sc. degree in Electrical and Electronic Engineering from Khulna University of Engineering & Technology, Khulna, Bangladesh and an M.Sc. in the same field from Rajshahi University of Engineering & Technology, Rajshahi, Bangladesh, with remarkable academic achievements, including Dean Awards and scholarships. With 23 publications in international journals and conferences, his research focuses on applications of AI in healthcare, agriculture, and security, including disease diagnosis, pest detection, and image cryptography. Md. Talukder's expertise spans advanced techniques in TensorFlow, Keras, SVM, Random Forest, and deep learning frameworks. He has also contributed to nuclear safety and international collaborations, reflecting his multidisciplinary skills. His passion for trustworthy AI aligns with his commitment to ethical and impactful technological solutions. Musarrat Nipun is a distinguished academic and researcher in the field of Computer Science, with a specialized focus on artificial intelligence and machine learning. Having earned a Master of Science degree in Computer Science from the University of Bedfordshire, UK, and an MBA with Distinction and best project award from York St John University, UK, Musarrat has a solid foundation in both technical and managerial disciplines. She has devoted several years to teaching at esteemed institutions such as Brunel University London (Pathway College) where she served as a Program Element Leader for the Department of Computer Science, showcasing leadership in curriculum development and student guidance. Currently, I am working as a permanent lecturer at Arden University in the Department of Computer Science and leading two core modules. In addition to teaching roles, Musarrat, throughout her tenure in academia, has been actively engaged in scholarly research, making significant contributions to the body of knowledge with numerous journal publications and authoring two chapters of books. Musarrat's commitment to excellence in education is further demonstrated by the pursuit of a teaching fellowship certification, for which she is currently awaiting results. Musarrat's contributions to both teaching and research underscore a dedication to advancing the field of computer science and a role as a leader in integrating artificial intelligence and machine learning into higher education.

Inhaltsangabe

Part I. Blockchain in Healthcare, 1. A Framework for the Integration of
Blockchain Technology in Healthcare Records Management Systems in
Kurdistan, 2. A Blockchain-Based Approach to Healthcare Data Security:
Leveraging Anomaly Detection and Smart Contracts, 3. Integrating AI,
Quantum Computing, and Blockchain for Secure Healthcare Data Management
Addressing Regulatory and Implementation Challenges, 4. Smart Wearables:
Revolutionizing Premier League Footballers with IoT and Blockchain
Technology, 5. Blockchain Technology for Healthcare Data Security and
Privacy, Part II. Security in Healthcare, 6. Adversarial Machine Learning
in Healthcare: Protecting AI Systems from Threats to Patient Safety and
Data Security, 7. Federated Learning in Healthcare: Distributed Machine
Learning for Privacy Preservation, 8. GAN and Explainable AI (XAI) for
Cybersecurity in Healthcare, 9. Impact of GDPR on Healthcare Data Security
Practices, Part III. Artificial Intelligence in Disease Prediction and
Analysis, 10. Leveraging AI in the Diagnosis and Management of Cerebral
Palsy in Children: A Case Study of Chattagram Maa-O-Shishu Hospital, 11.
Predicting New-Onset Diabetes Post-Transplantation in Kidney Patients
through Assessment of Medication Dosages: A Boosting Ensemble Machine
Learning Method, 12. Predicting Quality of Care Outcomes in Diabetes
Patients Using Boosted Tree Models: A Clinical Factor Analysis, Part IV.
Artificial Intelligence in Medical Imaging, 13. Deep Learning-Based Medical
Image Processing, 14. Deep Learning in Computerized Medical Imaging:
Diagnosing Lung Diseases (Pneumonia and COVID-19) from X-Rays, 15.
Exploring the Frontiers of Brain MRI Image Segmentation Using Deep Learning