Tao Hai
A novel and innovative blockchain-empowered federated learning approach for secure data sharing in smart city applications.
Hai, Tao; Wang, Dan; Seetharaman, Tamizharasi; Amelesh, M.; Sreejith, P.M.; Sharma, Vandana; Ibeke, Ebuka; Liu, Hong
Authors
Dan Wang
Tamizharasi Seetharaman
M. Amelesh
P.M. Sreejith
Vandana Sharma
Dr Ebuka Ibeke e.ibeke@rgu.ac.uk
Lecturer
Hong Liu
Contributors
Celestine Iwendi
Editor
Zakaria Boulouard
Editor
Natalia Kryvinska
Editor
Abstract
The very existence of smart cities forms the stepping stone in the evolution of many technological advancements in the future era. While smart cities have already grown in their way, the tremendous amount of data generated from them paves the way for new perspectives of development. This is because security and privacy remain to be the major constraint across smart city applications. Further, smart city applications such as smart homes, smart transportation, and smart healthcare are generating a huge amount of data every day and it is often complex to collect and manage all the data together at a single location. To address these constraints, this paper presents a novel and innovative blockchain-assisted federated learning approach for secure data sharing in IoT Smart Cities. Here, we implement a federated learning approach, where the process of learning is made in a distributed fashion. The use of blockchain in turn adds more security and resilience to smart city applications. The security analysis proves that the proposed approach offers comparatively better performance and remains more resistant to various security threats and vulnerabilities.
Citation
HAI, T., WANG, D., SEETHARAMAN, T., AMELESH, M, SREEJITH, P.M., SHARMA, V., IBEKE, E. and LIU, H. 2023. A novel and innovative blockchain-empowered federated learning approach for secure data sharing in smart city applications. In Iwendi, C., Boulouard, Z. and Kryvinska, N. (eds.) Proceedings of the 2023 International conference on advances in communication technology and computer engineering (ICACTCE'23): new artificial intelligence and the Internet of things based perspective and solutions, 23-24 February 2023, Bolton UK. Lecture notes in networks and systems, 735. Cham: Springer [online], pages 105-118. Available from: https://doi.org/10.1007/978-3-031-37164-6_9
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | Proceedings of the 2023 International conference on advances in communication technology and computer engineering (ICACTCE'23): new artificial intelligence and the Internet of things based perspective and solutions |
Start Date | Feb 24, 2023 |
End Date | Feb 25, 2023 |
Acceptance Date | Feb 6, 2023 |
Online Publication Date | Sep 24, 2023 |
Publication Date | Dec 31, 2023 |
Deposit Date | Feb 23, 2023 |
Publicly Available Date | Sep 25, 2024 |
Publisher | Springer |
Peer Reviewed | Peer Reviewed |
Pages | 105-118 |
Series Title | Lecture notes in networks and systems |
Series Number | 735 |
Series ISSN | 2367-3370; 2367-3389 |
Book Title | Proceedings of the Proceedings of the 2023 International conference on advances in communication technology and computer engineering (ICACTCE'23): new artificial intelligence and the Internet of things based perspective and solutions Bolton, UK |
ISBN | 9783031371639 |
DOI | https://doi.org/10.1007/978-3-031-37164-6_9 |
Keywords | Smart city; Federated learning; IOT; Secure data sharing; Blockchain |
Public URL | https://rgu-repository.worktribe.com/output/1893740 |
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