Defending Against Cyber Threats in the Smart Healthcare Ecosystem

Description

This book offers a practical guide to securing smart IoT-based healthcare devices against Cyberthreats with hands-on tools, threat modelling, risk scoring, and AI-enhanced defences. Healthcare is undergoing rapid digital transformation, with smart IoT devices from wearable monitors to implantable sensors integrated deeply into patient care and hospital workflows. While these innovations improve... Read more

This book offers a practical guide to securing smart IoT-based healthcare devices against Cyberthreats with hands-on tools, threat modelling, risk scoring, and AI-enhanced defences.

Healthcare is undergoing rapid digital transformation, with smart IoT devices from wearable monitors to implantable sensors integrated deeply into patient care and hospital workflows. While these innovations improve efficiency and outcomes, they also introduce new and severe cyber threats. Attackers now exploit vulnerabilities in IoT firmware, protocols, and networks, leading to risks that threaten patient safety, privacy, and trust. This book provides a practical, cyber-threat-focused guide to securing healthcare IoT environments. Unlike existing titles that emphasize general healthcare IT or clinical applications of AI, this volume focuses squarely on the cybersecurity challenges of IoT medical systems and shows how AI techniques can be leveraged to target and mitigate these threats. The chapters progress logically from real-world threat incidents to architectural vulnerabilities, and then to applied AI-based detection techniques. Readers are guided through:

Analyzing IoT-specific threats in healthcare environments.
Identifying vulnerabilities in devices and communication protocols.
Using AI/ML methods for intrusion and malware detection.
Applying threat modeling frameworks with AI-based risk scoring.
Implement federated learning to preserve patient privacy in collaborative detection.
Designing Zero Trust architectures adapted to healthcare IoT networks.
Apply explainable and ethical AI methods for transparent security decision-making.

Each chapter combines conceptual depth with practical labs, datasets, and exercises. Readers build hands-on skills using tools such as TensorFlow, PyTorch, Flower, Wireshark, and Nmap, and experiment with benchmark datasets such as CICIDS2017, BoT-IoT, and CVE/NVD vulnerabilities. By bridging theory with practice, this book serves as a professional reference for cybersecurity practitioners, a hands-on textbook for postgraduate courses, and a research guide for academics. Its dual orientation ensures relevance in industry, research, and education, preparing readers to secure the digital frontiers of modern healthcare.

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Chapter 1: Cyber Threats in Healthcare: Incidents, Challenges, and Emerging Trends. Chapter 2: Healthcare IoT Devices and Architectures: Vulnerabilities and Attack Surfaces. Chapter 3: Data Privacy and Patient Confidentiality using Lightweight Encryption and Steganography. Chapter 4: Future Trends and Emerging Technologies to Secure Healthcare Systems. Chapter 5: Threat Modeling & Risk Assessment for Medical Data. Chapter 6: AI-Driven Threat Detection Architecture. Chapter 7: Federated Learning and Privacy-Preserving AI in Healthcare. Chapter 8: Zero Trust Architecture for Healthcare. Chapter 9: Ethical AI and Bias Mitigation in Medical Decision Systems. Chapter 10: Self Assessment.

Author(s)

Biography

Dr. Akashdeep Bhardwaj is working as Professor and Director of Cybersecurity Centre of Excellence at UPES, Dehradun, India and is the CEO of Global Cybersecurity Association (GCA). An eminent IT Industry expert in areas such as Cybersecurity, Digital Forensics and IT Operations, Dr. Akashdeep mentors graduate, master’s and doctoral students and leads several projects. Dr. Akashdeep is a Post-Doctoral from Majmaah University, Saudi Arabia, Ph.D. in Computer Science, Post Graduate Diploma in Management (equivalent to MBA), and holds an Engineering Degree in Computer Science. Dr. Akashdeep has published over 200 research including journal manuscripts, copyrights, patents and books in highly referred international publications. Dr. Akashdeep worked as Technology Leader for several multinational organizations during his time in the IT industry. Dr. Akashdeep is certified in multiple technologies including Compliance Audits, Cybersecurity, and industry certifications in Microsoft, Cisco, and VMware technologies.

Dr. Keshav Sinha is an Assistant professor specializing in Cryptography and Network Security, with research focused on developing secure environments for Multimedia Transmission. His contributions extend beyond cryptography into Soft Computing, Humanities, and Cyber Policy, emphasizing innovation and flexibility in computer science. With a strong academic background and numerous publications in reputable conferences and journals, he has established himself as a dedicated researcher and educator. His expertise in cryptography and cybersecurity, coupled with his interdisciplinary approach, has positioned him as a thought leader in the field. His work in emerging security frameworks, regulatory challenges, and AI-driven cryptographic advancements continues to shape the future of digital security.

Dr. Sumitra is an Assistant Professor at UPES, Dehradun, India. She earned her Ph.D. from the Birla Institute of Technology and Science (BITS) Pilani, India. Her research primarily focuses on IoT security, artificial intelligence and machine learning (AI/ML), and federated learning. Dr. Sumitra has contributed extensively to the field through publications in reputed international journals, including the Journal of Network and Computer Applications and Internet of Things. Her research excellence was recognized with the Outstanding Research Article Award at the Doctoral Colloquium, BITS Pilani, for her work titled “RPL: An Explainable AI-based Routing Protocol for the Internet of Mobile Things.”

Defending Against Cyber Threats in the Smart Healthcare Ecosystem

Description

Table of Contents

Author(s)

Biography

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