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Federated Learning for the Internet of Things and Machine Learning

Submission Deadline: December 31, 2023

Guest Editors

Dr. Chamandeep Kaur
Department of Computer Science & Information  Technology, Jazan University, Saudi Arabia
Dr. Awatef Salem Balobaid
Department of Computer Science & Information  Technology, Jazan University, Saudi Arabia

Dr. Samar Mansoor Hassen
Department of Computer Science & Information  Technology, Jazan University, Saudi Arabia

Special Issue Information

Internet of Things (IoT) applications such as intelligent transportation and remote health monitoring have resulted in incredible advances in the quality of life. Massive devices and massive amounts of data necessitate the deployment of machine learning approaches in the IoT era to provide high-quality smart services. However, because of the risk of data misuse and leakage, IoT devices should not share personal data. Federated Learning (FL) has gained popularity in IoT applications in recent years as a distributed machine learning approach with data privacy. As FL technologies evolve, new challenges emerge, such as convergence rate analysis, device selection, resource allocation, and so on. To address these challenges, various theories, optimization algorithms, and sophisticated schemes have been proposed.
 
Furthermore, IoT applications can benefit from FL, and IoT systems can provide effective security. However, more research is needed to enable FL for IoT.
 
This Special Issue aims to bring together leading researchers and developers from industry and academia to present their research on FL for IoT and to promote the development of IoT. We welcome both original research and review papers.
 
Potential topics include but are not limited to the following:
• Architecture and protocol design in FL for IoT
• Machine Learning
• Applications and services in FL for IoT
• Convergence rate analysis for FL
• Advanced federated optimization algorithms for enabling FL in IoT
• Artificial intelligence empowered FL for IoT
• Blockchain empowered FL for IoT
• Communication, computation, and cache resource management in FL for IoT
• Intelligent resource allocation in FL for IoT
• Security and privacy issues in FL for IoT
• Implementation/testbed/deployment for FL
• Personalized FL for IoT

Manuscript Submission Information

Authors can submit their manuscripts through the Online Submission System. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to guest editors for perusal first.
 
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere. All manuscripts are thoroughly refereed through a blind peer-review process. A guide for authors and other relevant information for the submission of manuscripts is available on the Author Submission Guide page.
 
The Article Processing Charge for this special issue is 500 USD. Submitted papers should be well formatted and use good English. 

Published Papers

AI Driven Anomaly Detection in Network Traffic Using Hybrid CNN-GAN
Vuda Sreenivasa Rao*, R. Balakrishna, Yousef A. Baker El-Ebiary, Puneet Thapar, K. Aanandha Saravanan, and Sanjiv Rao Godla

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Toward an Intelligent Edge in the Internet of Things Era
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