CFDAS: A Customer-Centric and Fault-Tolerant Data Aggregation Scheme for Smart Grid in 6G Networks Keeping Unlinkability Under the Conception Industry 5.0
For Industry 5.0, people collaborate with artificial intelligence machines and robots, where the aim is beyond productivity. With customer-centric services, the smart grid evolves with the promotion of 6G and Industry 5.0. Data aggregation is necessary for analyzing accumulated consumption, adjusting demand and response, and predicting the trend. A host of data aggregation schemes for the smart grid considering security have been proposed. However, the hazard of information leaking still exists. Security features like fault-tolerance and unlinkability in aggregation schemes are hot problems that require discussions. In this paper, we propose our data aggregation scheme CFDAS for the smart grid with blockchain assistance in 6G networks under the concept of Industry 5.0. By employing a traditional three-layer structure, the aggregation process can be executed based on different consumption categories at fog nodes and control center. Formal verification proves that our scheme exhibits resistance to forgery attacks. Also, it satisfies usual security features like unlinkability and fault-tolerance. Compared to several recent schemes, ours performs well in time and communication overhead and is practical for 6G networks.
Authors
- Fan Wu (ORCID: https://orcid.org/0000-0001-9023-3569)
- Saru Kumari (ORCID: https://orcid.org/0000-0003-4929-5383)
- Chien‐Ming Chen (ORCID: https://orcid.org/0000-0002-6502-472X)
- Mohammed J. F. Alenazi (ORCID: https://orcid.org/0000-0001-6593-112X)
- Xiong Li (ORCID: https://orcid.org/0000-0001-6619-554X)
Institutions
- University of Electronic Science and Technology of China (CN)
- Xiamen University (CN)
- Nanjing University of Information Science and Technology (CN)
- King Saud University (SA)
- Chaudhary Charan Singh University (IN)
Publication Details
- Journal
- IEEE Transactions on Consumer Electronics
- Published
- 2024-11-29
- DOI
- https://doi.org/10.1109/tce.2024.3509437
- Primary Topic
- IoT and Edge/Fog Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00