Security and Privacy in IoMT

This book explores Internet of Medical Things (IoMT) security and privacy in electronic healthcare, addressing vulnerabilities in medical devices that expose patient data to cyber-attacks. It covers IoMT security challenges, potential attacks, and solutions considering resource constraints, network architecture, and communication protocols.

IoMT is revolutionizing the medical sector by providing personalized and targeted treatments and by facilitating seamless communication of medical data. IoMT devices are more trustworthy in monitoring and tracking due to higher accuracy levels, which also minimize human errors and inaccurate reporting. While the merits of IoMT devices are clear, they also pose severe privacy and security risks. Medical systems acquire, process, and perform decision-making based on this sensitive health information. Cyber attackers who exploit the flaws and weaknesses in these IoMT devices might well be able to penetrate the hospital network and gain unauthorized access to private patient data. Attacks on these IoMT devices also have the potential to endanger the patients' lives and cause serious physical harm.

In addition to outlining viable solutions that take into account constrained resources at IoMT end-devices, hybrid network architecture, application characteristics, and communication protocols, the book covers the core concepts of IoMT security and privacy. It describes both theoretical and practical aspects for those working in security in the IoMT, emphasizing the most significant potential IoT security issues and challenges.

Dr. Deepak Gupta is an eminent academician, who plays versatile roles and responsibilities juggling between lectures, research, publications, consultancy, community service, Ph.D. and post-doctorate supervision, etc. With 16 years of rich expertise in teaching and two years in industry, he focuses on rational and practical learning. He has contributed massive literature in the fields of human–computer interaction, intelligent data analysis, nature-inspired computing, machine learning and soft computing. He is working as Assistant Professor at Maharaja Agrasen Institute of Technology (GGSIPU), Delhi, India. He has served as Editor-in-Chief, Guest Editor, Associate Editor for SCI and various other reputed journals (IEEE, Elsevier, Springer, Wiley and MDPI). He has actively been on the organizing end of various reputed international conferences. He completed his Post-Doc from Internet of Things research group, National Institute of Telecommunications (Inatel), Brazil in 2018 and eHealth and Telemedicine Group (GTe), University of Valladolid (UVA), Spain in 2019, Federal University of Piauí (UFPI), Teresina - Pi, Brazil in 2021 and Ph.D. from Dr. APJ Abdul Kalam Technical University, India in 2017. He has authored/edited 70 books with national/international level publishers (IEEE Press, Elsevier, Springer, Wiley, CRC, DeGruyter). He has published 330 scientific research publications in reputed international journals and conferences including 213 SCI indexed journals of IEEE, Elsevier, Springer, Wiley and many more. He has also granted/published 8 patents. He is the recipient of 2021 IEEE System Council Best Paper Award and Highly Cited Paper Award in Applied Sciences Journal. He has been featured in the list of top 2% scientist/researcher database in the world in 2019, 2020, 2022 with Rank 51 in AI & Image Processing, Rank 423 in India overall and Rank 80604 in World overall.

Dr. Anuj Kumar Singh is working as Associate Professor in the Department of Computer Science and Engineering at Amity University Madhya Pradesh, India. He has more than 20 years of teaching experience in technical education. He holds a Ph.D. degree in the field of Computer Science and Engineering from Dr. A.P.J. Abdul Kalam Technical University, Lucknow. He gained a M.Tech degree with First Distinction from Panjab University, Chandigarh and a B.Tech degree with First Honours from U.P.T.U Lucknow in Computer Science and Engineering. In addition to these, he also qualified UGC NET. Having published more than 40 research papers in journals and conferences including SCIE and Scopus, he has also authored one book and edited seven. He has also filed five patents. He has also supervised more than ten dissertations at PG level. His areas of specialization include intelligent systems, cryptography, network and information security, cybersecurity, blockchain technology, and algorithm design.

Dr. Yu-Dong (Eugene) Zhang serves as a Chair Professor at the School of Computing and Mathematical Sciences, University of Leicester, UK. His research interests include deep learning and medical image analysis. He is a Fellow of IET, Fellow of EAI, and Fellow of BCS. He is the Senior Member of IEEE, IES, and ACM. He is a Distinguished Speaker of ACM. He was included in the Most Cited Chinese Researchers (Computer Science) by Elsevier from 2014 to 2018. He was 2019, 2021 and 2022 recipient of Clarivate Highly Cited Researcher. He is included in World’s Top 2% Scientist by Stanford University from 2020 to 2022. He won the Emerald Citation of Excellence 2017, MDPI Top 10 Most Cited Papers 2015, Information Fusion 2022 Best Paper Award, etc. His three papers are included in UK Research Excellence Framework (REF) 2021. Up to 2023 he has (co)authored over 400 peer-reviewed articles in journals: Ann Oncol, JACC, JAMA Psychiatry, IJIM, Inf Fus, IEEE TFS, etc. He has more than 60 ESI Highly Cited Papers and 6 ESI Hot Papers in his (co)authored publications. He is the editor of Neural Networks, IEEE TITS, IEEE TCSVT, IEEE JBHI, etc. He has conducted many successful industrial projects and academic grants from NIH, Royal Society, GCRF, EPSRC, MRC, BBSRC, Hope, British Council, Fight for Sight, and NSFC. He has given over 120 invited talks at international conferences, universities, and companies, including Harvard University, University of Birmingham, University of Sheffield, etc. He has served as (Co-)Chair for more than 60 international conferences and workshops (including more than 20 IEEE or ACM conferences).