The fifth generation (5G) and beyond the fifth generation (B5G) networks have shown significant promise in enhancing the efficiency and coverage of the Internet of Things (IoT) over the last couple of years. The Internet of Things (IoT) will certainly play a significant part in 5G and B5G networks, where massive machine-type communications (mMTC) are crucial and demanding use cases. Meanwhile, 5G and B5G can be seen as the basis for realizing the full potential of IoT. More smart devices will be incorporated into 5G and B5G networks as IoT grows, creating massive amounts of real-time data.

However, security and privacy concerns may arise as the volume of data generation and data sharing increases. Likewise, integrating IoT devices and platforms into the 5G and B5G paradigms raises several issues that must be solved prior to deployment. The expected high traffic needs, low-latency, and deterministic delivery requirements of IoT and machine-to-machine (M2M) communications can only be addressed by revolutionary innovations in architecture, communication, and networking technologies.

The aim of this Special Issue is to bring together original research and review articles discussing solutions to solve challenging issues such as privacy leakage, data confidentiality, and flexible accessibility in 5G and B5G wireless networks. Submissions can include cutting-edge technologies such as artificial intelligence (AI), machine learning (ML), quantum machine learning (QML), blockchain, terahertz (THz) communication, fog/edge computing, visible light communication (VLC), etc.

Potential topics include but are not limited to the following:

• Security and privacy issues for 5G and B5G enabled IoT networks
• Integrating IoT into 5G and B5G networks
• Device-to-device (D2D) and cognitive communications
• Blockchain-based security protocols for 5G and B5G enabled IoT networks
• Novel frameworks and algorithms based on existing and upcoming technologies to enhance the scalability and security for 5G and B5G enabled IoT networks
• Cloud, fog, and edge computing architecture for 5G and B5G enabled IoT networks
• Machine learning algorithms for 5G and B5G enabled IoT networks
• Reinforcement learning based intelligent applications in 5G and B5G enabled IoT networks
• Federated learning for 5G and B5G enabled IoT networks