Riassunto
Cybersecurity for Healthcare Systems in the Internet of Medical Things Era is driven by the imperative to address the intricate convergence of healthcare, technology, and security. In response to the burgeoning challenges presented by the Internet of Medical Things (IoMT), this book is designed to be an indispensable resource for computer systems experts, healthcare staff, and executives. It goes beyond the surface, offering strategic insights and actionable strategies that encompass not only the IoMT landscape but also the intersection of artificial intelligence, signal processing, and cyber security. Cybersecurity for Healthcare Systems in the IoMT Era serves as a problem-solving compass for a diverse readership in the healthcare landscape. For healthcare professionals and IT leaders, the book untangles the complexities of integrating and securing Internet of Medical Things (IoMT) devices, offering a roadmap for understanding and navigating this rapidly evolving terrain. Biomedical engineers, burdened with strategic and everyday decisions, find in this book strategic insights and actionable strategies, empowering them to make informed choices amidst the ever-changing challenges posed by technology and cybersecurity threats. The authors present a comprehensive guide that not only elucidates the challenges and opportunities presented by IoMT but also explores how the synergy of AI and signal processing can elevate healthcare systems. This integration is crucial in deciphering the intricate nuances of medical data, enhancing diagnostics, and fortifying the security of interconnected healthcare networks.
Informazioni sugli autori
Janmenjoy Nayak is an Assistant Professor, P.G. Department of Computer Science, Maharaja Sriram Chandra Bhanja Deo University, Baripada, Odisha, India. He has been a Gold Medallist in Computer Science twice in his career, and has been awarded the “Innovation in Science Pursuit for Inspired Research” (INSPIRE) Research Fellowship from the Department of Science & Technology, Government of India (at both Junior Research Fellow and Senior Research Fellow level) and Best Researcher Award from Jawaharlal Nehru University of Technology, Kakinada, Andhra Pradesh for the academic year 2018–19. He has received many other awards from national and international academic agencies. Dr. Nayak has edited 19 books and 8 special issues on the applications of computational intelligence, soft computing, and pattern recognition, which have been published by Springer and Inderscience. He has published more than 190 refereed articles in various book chapters, conferences, and peer-reviewed journals of Elsevier, Inderscience, Springer, the Institute of Electrical and Electronics Engineers (IEEE), and others. He has also served as a reviewer for more than 100 journals and conferences produced by the IEEE, the Association for Computing Machinery (ACM), Springer, Elsevier, Wiley, and Inderscience. He has 11 years of experience in both teaching and research. Dr. Nayak is a senior member of the IEEE and a life member of societies such as the Soft Computing Research Society (SCRS), the Computer Society of India (CSI India), the Orissa Information Technology Society (OITS), the Orissa Mathematical Society (OMS), and the International Association of Engineers (IAENG), Hong Kong. He has successfully conducted and is associated with 14 internationally renowned series conferences such as ICCIDM, HIS, ARIAM, CIPR, and SCDA. His areas of interest include data mining, nature-inspired algorithms, and soft computing.
Manohar Mishra is an Associate Professor in the Department of Electronics and Electrical Engineering, Faculty of Engineering and Technology, Siksha ‘O’ Anusandhan Deemed to be University, Bhubaneswar, Odisha, India. He received his PhD in Electrical Engineering, MTech in Power Electronics and Drives, and BTech in Electrical Engineering in 2017, 2012, and 2008, respectively. He has published more than 50 research papers in various peer-reviewed international journals and conferences. He has edited three research books, and has served as a reviewer for journal publishers such as the Institute of Electrical and Electronics Engineers (IEEE), Springer, Elsevier, and Inderscience. At present, he has more than 10 years of teaching experience in the field of electrical engineering. He is a senior member of the IEEE, and is currently guiding four PhD scholars. His areas of interest include power system analysis, power system protection, signal processing, power quality, distribution generation systems, and micro-grids. He has served as Convener and Volume Editor of the International Conference on Innovation in Electrical Power Engineering, Communication and Computing Technology (IEPCCT-2019, IEPCCT-2021) and the International Conference on Green Technology for Smart City and Society (GTSCS-2020). Currently, he is serving as Guest Editor for different journals such as International Journal of Power Electronics (Inderscience), International Journal of Innovative Computing and Application (Inderscience), and Neural Computing and Application (Springer).
Khan Muhammad received his PhD in Digital Contents from Sejong University, South Korea in February 2019. He was an Assistant Professor in the Department of Software, Sejong University from March 2019 to February 2022. He is currently the director of Visual Analytics for Knowledge Laboratory (VIS2KNOW Lab) and an Associate Professor (Tenure-Track) in the Department of Applied AI, School of Convergence, College of Computing and Informatics, Sungkyunkwan University, Seoul, South Korea. His research interests include intelligent video surveillance, medical image analysis, information security, video summarization, multimedia data analysis, computer vision, and smart cities. He has registered 10 patents and contributed more than 220 papers in peer-reviewed journals and conference proceedings in his research areas. He is an Associate Editor/Editorial Board Member for more than 15 journals. He was among the most highly cited researchers in 2021 and 2022, according to the Web of Science (Clarivate).
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