Next-generation wireless network implementation technology supports vital tasks and personalized services in multiple application fields. Wireless networks have been significantly improved by developing network slicing, virtualization, massive MIMO, artificial intelligence, and deep learning technologies. These technological breakthroughs enable the next generation of wireless networks to support extremely high capacity, large-scale connections, and ultra-low latency communications. The benefits to society will be enormous. These exciting wireless network functions are rapidly emerging, and at the same time, many security and privacy issues are imminent.

Next-generation wireless network security faces many devices and data and complex application environments. Existing technology is subject to many practical security restrictions. Additionally, the devices in the network usually have limited computing power, storage, and energy, so it is unrealistic to use expensive encryption primitives for security and privacy solutions. Therefore, many technologies are ineffective or inefficient. In addition, new innovative technologies (such as blockchain, artificial intelligence, deep learning, 5G, etc.) have been introduced into wireless networks to meet new business needs, such as smart cities, smart grids, etc. Therefore, the security of the next-generation wireless network is facing both traditional and new problems after technology integration. These problems may threaten the next-generation wireless network's security, trust, and privacy. Therefore, it is particularly urgent to combine various privacy protection schemes and privacy-enhancing technology to protect the next-generation network security.

This Special Issue will focus on cutting-edge research in academia and industry. It aims to solicit original research and review articles concerning the security, trust, and privacy challenges in next-generation wireless networks.

Potential topics include but are not limited to the following:

• Privacy-enhancing and cryptographic technologies in wireless networks
• Security authentication and privacy protection of mass devices in 5G wireless networks
• Blockchain-based privacy protection in wireless networks
• Artificial intelligence and deep learning in wireless networks
• Privacy data disclosure and detection in wireless networks
• Security based on edge computing in wireless networks
• Security and privacy management of multimedia on the Internet of Multimedia Things
• Malware detection and analysis on the Internet of Multimedia Things
• Social network mining and recommendation
• Attack privacy mechanisms and models of wireless networks or Wireless Body Area Network
• Blockchain for trustworthy IIoT/CPS-based applications
• Embedded systems security
• Cyber threat intelligence for AI and IIoT/CPS
• Privacy-preserving Machine Learning
• Threats and mitigations for IoT based Federated Learning