What is it about?

Wael Eid Fathy currently works at the Department of Computer Science, Helwan University, since 2014. Wael does research in Machine Learning, Deep Learning, and Medical Image Processing. I received the B.Sc, PreM. Sc, and Master's degrees in Computer Science in 2013, 2015, and 2019 respectively. My research interests include the areas of Machine learning, Image Processing, Deep Learning, Privacy Preservation, Blockchain, and Federated learning. Recently, I have been a Ph.D. student at the school of engineering and information technology, UNSW, Canberra.

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Why is it important?

This work is considered guidance for new researchers interested in integrating blockchain and federated learning to secure IoT ecosystems.

Perspectives

This paper has discussed Federated Learning, blockchain, and their integration in IoT systems to secure decision-making and data analytics. Blockchain-based FL architectures have recently been promising solutions for addressing the security and privacy problems associated with data analytics in IoT environments. However, these architectures create the possibility of new security, privacy, and efficiency concerns. Therefore, new enhanced architectures and algorithms should investigate and address these concerns. This survey examined blockchain and FL to show the significance of combining the two technologies to enable secure, effective, and robust IoT applications. Afterward, FL security and privacy threats are investigated along with the recently proposed solution for those threats. Next, this work provides comprehensive literature about blockchain-based FL solutions for IoT applications. Then, the lessons learned from this survey are listed. Finally, this work has highlighted several potential challenges and future directions for blockchain-based FL IoT architectures, which will necessitate further research and investigation in future research.

Wael Issa
University of New South Wales

Read the Original

This page is a summary of: Blockchain-based Federated Learning for Securing Internet of Things: A Comprehensive Survey, ACM Computing Surveys, September 2022, ACM (Association for Computing Machinery), DOI: 10.1145/3560816.
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