Securing the Future of Digital Medicine: AI-Driven Cyber Defense Frameworks for Modern Healthcare Ecosystems

Submission Deadline: 31 May 2027 View: 623 Submit to Special Issue

Guest Editor(s)

Prof. Fahad Alturise

Email: falturise@qu.edu.sa

Affiliation: Department of Cybersecurity, College of Computer, Qassim University, Buraidah, Saudi Arabia

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Research Interests: e-learning, machine learning, e-commerce, e-government, artificial intelligence, information technology strategy and management, nformation technology risk management, information security, network security

Prof. Abdullah Alabdulatif

Email: a.alabdulatif@qu.edu.sa

Affiliation: Department of Cybersecurity, College of Computer, Qassim University, Buraydah, Saudi Arabia

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Research Interests: privacy & access control, healthcare security, Iot security, blockchain security, network security

Dr. Saeed M. Alshahrani

Email: salshahrani@su.edu.sa

Affiliation: Department of Computer Science College of Computing and Information Technology Shaqra University, Shaqra, Riyadh, Saudi Arabia

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Research Interests: AI, big data, IoT IoMT, blockchain

Dr. Haifa Saleh Alfurayj

Email: h.alfureej@qu.edu.sa

Affiliation: Department of Computer Science, College of Computer, Qassim University, Buraidah, Saudi Arabia

Homepage:

Research Interests: data knowledge, machine learning, big data, artificial intelligence

Summary

The rapid digitization of contemporary healthcare networks, driven by interconnected medical devices, cloud-based data repositories, and automated clinical systems, has fundamentally transformed patient care. However, this expansive connectivity significantly widens the cyberattack surface, making health infrastructures vulnerable to sophisticated threats. Because medical ecosystems handle highly sensitive data where system availability directly impacts human lives, conventional security measures are no longer adequate.

This Special Issue aims to provide a platform for researchers and practitioners to bridge the gap between artificial intelligence, automation, and cybersecurity by presenting advancements from theoretical models to practical implementations, ensuring privacy, trust, and resilience. The ultimate goal is to compile rigorous research that advances intelligent cyber defense frameworks for digital medicine. We welcome original research, case studies, and comprehensive reviews that bridge the gap between artificial intelligence, automation, and cybersecurity. Our objective is to capture advancements—ranging from theoretical security models to practical implementations—ensuring privacy, trust, and resilience across next‑generation digital health environments.

Recommended Topics for Submission (Include but are not limited to):
·Machine Learning and Deep Learning for Medical Threat Detection
·Security and Privacy in the Internet of Medical Things (IoMT)
·Soft Computing and Evolutionary Algorithms for Network Defense
·Federated Learning and Privacy‑Preserving AI for Clinical Data
·Blockchain and Distributed Ledger Technologies for Secure Health Records
·Zero‑Trust Architectures and Access Control in Hospital Environments
·Intrusion Detection and Prevention Systems for Biomedical Infrastructure
·Cloud and Edge Computing Security for Digital Health Applications
·Cryptographic Protocols and Data Anonymization in Medicine
·Risk Assessment and Automated Vulnerability Mitigation in Healthcare

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