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AI-driven Cybersecurity in Cyber Physical Systems enabled Healthcare, Current Challenges, Requirements and Future research Foresights

Submission Deadline: 31 March 2023 (closed)

Guest Editors

Dr. Jehad Ali, Ajou University, South Korea.
Dr. Sahib Khan, University of Engineering and Technology Mardan, Pakistan.
Mr. Muhammad Adil, Embry-Riddle Aeronautical University, USA.


With the gradual integration of Internet of Things (IoT), the digital healthcare industry has become omnipresent, complex, sophisticated, autonomous, and efficient. Thus, today's cyber-physical systems (CPS), which include healthcare gadgets, patient wearable devices, medical equipment, intelligent implantable medical devices (IMDs), and smart sensors, etc, have caught the interest of both academics and industry. Digital healthcare-based CPS are distinguished by a bunch of possibilities for both pros-consumers (patients, caretaker, and their families) and service providers (doctors, nurses, and other involved entities). Nonetheless, the integration of IoT with healthcare is hampered by a number of flaws, including interoperability, security, and high reliability. Among these problems, the adoption of appropriate security measures is one of the most worrisome concerns that healthcare-based CPSs confront. However, the fortification of conventional intrusion detection (IDS), prevention systems (IPS), and firewalls with access control tools frequently fail to identify devastating attacks on these networks, which could be life-threatening attacks.

To address these challenges, the development of more sophisticated and intelligent security methods is critical to ensuring the continuation and security of healthcare-based CPS services. Artificial intelligence (AI)-driven solutions, for example, are a recent development that allows the smooth and secure handling of heterogeneous data while building extremely decisive attack patterns in order to properly predict the hacker behavior and prevent them before any infiltration. Apart from this, game-theoretic techniques have emerged as preeminent possibilities for cyber defense because of their ability to best solve the complex decision-making challenges that arise in cyberspace.

The purpose of this Special Issue is to bring together leading researchers from academia and industry to discuss their visions, challenges, recent findings, and advances related to the application of artificial intelligence-based cyber security for the digital healthcare ecosystem.


• Case-studies, applications, and prototypes for healthcare cyber security
• New framework, algorithms, and protocol designs for AI-based healthcare CPSs
• Machine learning driven IDS/IPS solutions for healthcare CPSs
• Simulation, testing and formal verification of AI-based security solutions for healthcare
• Big data analytic frameworks for AI-powered healthcare CPSs
• Networking and Computing Architecture AI-based healthcare CPSs
• Cloud/grid/edge computing for healthcare CPSs
• Data-driven optimization of AI-based healthcare networks
• Game theory based secure and trustable solutions for healthcare systems
• Energy-efficient network operations for healthcare CPSs via AI/ML
• Proactive network monitoring architecture for healthcare CPSs
• Exploiting 5G and Beyond for AI-aided healthcare solutions
• Self-Learning and adaptive networking protocols for real-world CPSs
• AI based security solutions for IMDs, smart sensors, wearables, etc
• Deep and reinforcement learning based security solutions for attack prediction in CPSs
• Other standards, policies and regulations for integrating IoT paradigms in CPSs
• Human-machine interaction for healthcare cyber security

Published Papers

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