SDAG: blockchain-enabled model for secure data awareness in smart grids
Sani, Abubakar Sadiq, Yuan, Dong and Dong, Zhao Yang (2023) SDAG: blockchain-enabled model for secure data awareness in smart grids. In: Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2023 IEEE. 16th - 19th January 2023. Power & Energy Society Innovative Smart Grid Technologies . 2023 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT) DOI: 10.1109/ISGT51731.2023 16-19 Jan. 2023, Piscataway, New Jersey, pp. 1-5. ISBN 978-1665453554; 978-1665453561 (doi:https://doi.org/10.1109/ISGT51731.2023.10066338)
|
PDF (AAM)
38389_SANI_SDAG_Blockchain_enabled_model_for_secure_data_awareness_in_smart_grids (1).pdf - Accepted Version Download (334kB) | Preview |
Abstract
We introduce SDAG, a blockchain-enabled secure data awareness model by which energy nodes can provide visibility into energy operations without involving energy operators in the smart grids. SDAG consists of a registration protocol (RPro) for assigning a cryptographic identity to an energy node and a data-aware protocol (DAPro) for executing data awareness with the support of a shared secret session key and SDAG smart contracts, which facilitate data awareness consensus amongst energy nodes. SDAG satisfies the smart grid's data awareness security requirements, which include correctness of data, assurance of energy node identity, and fairness of data awareness transactions such as energy node registration. As a proof of concept, we apply our model to mitigate a recent issue on the loss of State Estimator (SE) due to contracting data in a real-world energy grid.
Item Type: | Conference Proceedings |
---|---|
Title of Proceedings: | Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2023 IEEE. 16th - 19th January 2023 |
Uncontrolled Keywords: | data awareness; security; blockchain; smart grids; key exchange |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
Faculty / School / Research Centre / Research Group: | Faculty of Engineering & Science Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS) |
Related URLs: | |
Last Modified: | 25 Sep 2023 13:10 |
URI: | http://gala.gre.ac.uk/id/eprint/38389 |
Actions (login required)
View Item |
Downloads
Downloads per month over past year