AI-Driven Cybersecurity for Intelligent Healthcare Systems - Brossura

Brossura

ISBN 10: 0443277613 ISBN 13: 9780443277610

Casa editrice: Academic Press, 2026

Riassunto

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.

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Informazioni sugli autori

Dr. Balamurugan Balusamy is currently working as an Associate Dean Student in Shiv Nadar Institution of Eminence, Delhi-NCR. He is part of the Top 2% Scientists Worldwide 2023 by Stanford University in the area of Data Science/AI/ML. He is also an Adjunct Professor in the Department of Computer Science and Information Engineering, Taylor University, Malaysia. His contributions focus on engineering education, blockchain, and data sciences

Dr Prithi Samuel is currently working as an assistant professor in the Department of Computational Intelligence at SRM Institute of Sci?ence and Technology, Kattankulathur Campus, Chennai. She has completed her Ph.D. in Information and Communication Engineering from Anna University, Chennai. She has got over 15 years of teaching experience in reputed engineering colleges in Tamil Nadu. She is a pioneer researcher in the areas of Automata Theory, Machine Learn?ing, Deep Learning, Computational Intelligence Techniques, and the Internet of Things. She has published more than 25 papers in leading SCI and Scopus Journals and more than 25 papers in International Conferences and published 1 book and more than 10 book chapters in Wiley, Taylor and Francis, Springer, and Elsevier and published 4 patents and 2 patent grants. She is an active IEEE, ACM Member and holds an ISTE and IAENG lifetime membership

Sunita Chand is an assistant professor in the Department of Department of Computer Science, Hansraj College, University of Delhi. She is a pioneer researcher in the areas of image processing, cyber security, deep learning, natural language processing, and nature inspired algorithms. She has published papers in leading international journals and international conferences and published book chapters in IEEE, Springer, Inderscience, AIP, ACM and Elsevier.

Mahmoud Ahmad Al-Khasawneh is a faculty member in the School of Computing Skyline University College, Sharjah UAE.

His scholarly pursuits span a diverse array of fields within computer science. He has authored numerous papers in esteemed, peer-reviewed journals across leading publishers such as IEEE, Springer, Wiley, Hindawi, and MDPI. His research interests encompass Security, Image Encryption, Wireless Networks, Blockchain, Internet of Things, and Big Data. With a commitment to advancing knowledge and solving contemporary challenges in these domains, he actively engages in research, teaching, and mentorship, contributing to the academic and professional development of his students and peers. Driven by a passion for innovation and a dedication to excellence, he continues to make significant contributions to the field, shaping the future of technology and its applications.

Dalla quarta di copertina

AI-Driven Cybersecurity for Intelligent Healthcare Systems explores the intersection between AI, cybersecurity, and healthcare. It offers detailed insights into the unique cybersecurity challenges faced by the healthcare sector and the role of AI in addressing these challenges. This book presents case studies and real-world applications to illustrate the effectiveness of these solutions. Additionally, it 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.

Dettagli dell'edizione

• Editore: Academic Press
• Data di pubblicazione: 2026
• Lingua: Inglese
• ISBN 10: 0443277613
• ISBN 13: 9780443277610
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 342
• Redattore: Balusamy
• Contatto del produttore: non disponibile
• Persona responsabile: LSWR Group; b.criscuolo@lswr.it; ; Via Spadolini, 7; Milano; Italia