The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Privacy-Preserving Energy Trading Using Consortium Blockchain in Smart Grid
Abstract
Implementing blockchain techniques has enabled secure smart trading in many realms, e.g. neighboring energy trading. However, trading information recorded on the blockchain also brings privacy concerns. Attackers can utilize data mining algorithms to obtain users' privacy, specially, when the user group is located in nearby geographic positions. In this paper, we present a consortium blockchain-oriented approach to solve the problem of privacy leakage without restricting trading functions. The proposed approach mainly addresses energy trading users' privacy in smart grid and screens the distribution of energy sale of sellers deriving from the fact that various energy trading volumes can be mined to detect its relationships with other information, such as physical location and energy usage. Experiment evaluations have demonstrated the effectiveness of the proposed approach.
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Cites
Aitzhan, N. Z., & Svetinovic, D. (2018) · IEEE Transactions on Dependable and Secure Computing · doi:10.1109/tdsc.2016.2616861 · Cited by 1,297
Kang, J., Yu, R., Huang, X., Maharjan, S., Zhang, Y., & Hossain, E. (2017) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2017.2709784 · Cited by 1,139
Consortium Blockchain for Secure Energy Trading in Industrial Internet of Things
Li, Z., Kang, J., Yu, R., Ye, D., Deng, Q., & Zhang, Y. (2017) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2017.2786307 · Cited by 1,103
Dependable Demand Response Management in the Smart Grid: A Stackelberg Game Approach
Maharjan, S., Zhu, Q., Zhang, Y., Gjessing, S., & Basar, T. (2013) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2012.2223766 · Cited by 783
Control Strategies for Microgrids With Distributed Energy Storage Systems: An Overview
Morstyn, T., Hredzak, B., & Agelidis, V. G. (2018) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2016.2637958 · Cited by 454
Home M2M networks: Architectures, standards, and QoS improvement
Zhang, Y., Yu, R., Xie, S., Yao, W., Xiao, Y., & Guizani, M. (2011) · IEEE Communications Magazine · doi:10.1109/mcom.2011.5741145 · Cited by 431
Distributed Energy Trading in Microgrids: A Game-Theoretic Model and Its Equilibrium Analysis
Lee, J., Guo, J., Choi, J. K., & Zukerman, M. (2015) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2014.2387340 · Cited by 396
Park, S., Lee, J., Bae, S., Hwang, G., & Choi, J. K. (2016) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2016.2532842 · Cited by 191
Optimal Pricing and Energy Scheduling for Hybrid Energy Trading Market in Future Smart Grid
Wu, Y., Tan, X., Qian, L., Tsang, D. H. K., Song, W., & Yu, L. J. (2015) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2015.2426052 · Cited by 132
Self-citationZhang, X., Dou, W., Pei, J., Nepal, ., Yang, C., Liu, C., & Chen, J. (2014) · IEEE Transactions on Computers · doi:10.1109/tc.2014.2360516 · Cited by 114
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Blockchain for 5G and beyond networks: A state of the art survey
Nguyen, D. C., Pathirana, P. N., Ding, M., & Seneviratne, A. (2020) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2020.102693 · Cited by 412
DeepCoin: A Novel Deep Learning and Blockchain-Based Energy Exchange Framework for Smart Grids
Ferrag, M. A., & Maglaras, L. (2020) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2019.2922936 · Cited by 358
Blockchain for Internet of Energy management: Review, solutions, and challenges
Miglani, A., Kumar, N., Chamola, V., & Zeadally, S. (2020) · Computer Communications · doi:10.1016/j.comcom.2020.01.014 · Cited by 346
Blockchain-enabled Federated Learning: A Survey
Qu, Y., Uddin, M. P., Gan, C., Xiang, Y., Gao, L., & Yearwood, J. (2023) · ACM Computing Surveys · doi:10.1145/3524104 · Cited by 286
Haque, A. K. M. B., Bhushan, B., & Dhiman, G. (2022) · Expert Systems · doi:10.1111/exsy.12753 · Cited by 271
Metadata
- Authors
- Gai, K., Wu, Y., Zhu, L., Qiu, M., & Shen, M.
- Venue
- IEEE Transactions on Industrial Informatics
- Published
- 2019-06
- Volume
- 15
- Issue
- 6
- Pages
- 3548-3558
- ISSN
- 1551-3203 (ISSN-L)
- 1941-0050
- OpenAlex
- W2909202584
- Cited by
- 573
- References
- 19
- FWCI
- 115.28
- Type
- journal article
- Language
- en
- Open access
- closed
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- Gai, K., Wu, Y., Zhu, L., Qiu, M., & Shen, M. (2019). Privacy-Preserving Energy Trading Using Consortium Blockchain in Smart Grid. IEEE Transactions on Industrial Informatics. https://doi.org/10.1109/tii.2019.2893433
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
