Journal: Journal of Cyber Security

🔗SI URL: https://www.techscience.com/JCS/special_detail/privacy_computing

📅 Submission Deadline: 31 August 2025

✉️Email Enquiry: [email protected]

🌟 Guest Editors:

Dr. Junfeng Miao, Henan Normal University, Hennan, 453007, China

Dr. Nan Xiao, University of Science and Technology Beijing, Beijing，100083, China

Dr. Xue Miao, Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100083, China

🔍 Summary:

With the continuous evolution of Internet of Things (IoT) technology, we are entering a new era of interconnected and data-driven everything. However, while IoT brings convenience and efficiency, it also faces severe challenges in data privacy and security. To address these challenges, privacy computing and federated learning, as emerging technological paradigms, are gradually becoming key drivers for the development of the next generation of IoT. Research on how to combine privacy computing with federated learning to build a more secure and efficient IoT data processing framework, enhancing data value while protecting user privacy. Therefore, in order to better serve the Future Generation of IoT with privacy computing and federated learning, new theories, technologies, architectures, algorithms, authentication, and mechanisms need to be proposed.

The topics of interest in this special issue include (but are not limited to):

-Privacy computing for future generation IoT

-Federated learning for future generation IoT

-Edge and fog computing for future generation IoT

-Blockchain enables edge intelligence for future generation IoT

-Privacy protection authentication in IoT/ future generation IoT

-Data security for future generation IoT

-Access control for future generation IoT

-Resource management for future generation IoT

-The security architecture of edge intelligence for future generation IoT

Key Words:

Privacy computing, Federated learning, Privacy protection, Future Generation IoT