Due to recent advancements in microelectromechanical systems (MEMS) and sensors, it is now possible to develop secure healthcare systems (SHS) using the Internet of Things (IoT). In these networks, every member device has to collect and share data while ensuring secure and authentic communication sessions. These systems are further strengthened from a device and data security perspective if artificial intelligence (AI)-based approaches are integrated with IoT networks. For example, in SHS, wearable devices are used to collect patient’s data to generate medical reports which are shared with professionals and experts for a better and more timely diagnosis of diseases.

However, the wireless communication mechanisms used to share these reports are vulnerable to numerous intruder attacks as the authenticity of both data and source devices is necessary to ensure the reliability of the SHS. Data integrity is the highest priority in SHS as altered or corrupted data may lead to numerous health issues. Additionally, hiding the identity of individuals, such as patients or doctors, and ensuring the authenticity of both data and member device are among the most challenging issues in the development of SHS.

The objective of this Special Issue is to attract and encourage the submission of novel contributions, techniques, and data analytic approaches for smart healthcare systems (preferably AI-based), to ensure the integrity and authenticity of data and member devices respectively. Furthermore, submitted papers should highlight and reflect the potential of IoT and AI in resolving the aforementioned issues, which are tightly coupled with the realization process of secure healthcare systems. We welcome researchers from both academia and industry to provide their state-of-the-art technologies and ideas covering all aspects of security and privacy solutions for these applications.

Potential topics include but are not limited to the following:

• AI-enabled device-to-device communication in smart healthcare
• Mutual authentication of both devices and servers in smart healthcare applications
• Applications of mathematical modeling in SHS
• Secure communication sessions between member devices and between devices and servers in smart healthcare applications
• Secure communication sessions between server devices in smart healthcare applications
• Security and privacy issues in AI-enabled SHS, IoT-enabled SHS, and in IoT and AI-enabled SHS
• Security and privacy issues related to the data collection and sharing process in SHS
• Security and privacy issues in multimedia data analytics in SHS
• Cryptographic mechanisms, algorithms, or protocols for SHS
• Protection systems against personal identity theft
• Media cloud applications for SHS
• Cyber security for the SHS
• Blockchain-enabled authenticity and privacy of member devices and servers in SHS