Privacy-Preserving Smart Metering with Authentication in a Smart Grid
- Authors
- Hur, Jun Beom; Koo, Dong Young; Shin, Young Joo
- Issue Date
- 12월-2015
- Publisher
- MDPI
- Keywords
- smart grid; smart metering; privacy; security; data aggregation
- Citation
- APPLIED SCIENCES-BASEL, v.5, no.4, pp.1503 - 1527
- Indexed
- SCIE
SCOPUS
- Journal Title
- APPLIED SCIENCES-BASEL
- Volume
- 5
- Number
- 4
- Start Page
- 1503
- End Page
- 1527
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/91798
- DOI
- 10.3390/app5041503
- ISSN
- 2076-3417
- Abstract
- The traditional security objectives of smart grids have been availability, integrity, and confidentiality. However, as the grids incorporate smart metering and load management, user and corporate privacy is increasingly becoming an issue in smart grid networks. Although transmitting current power consumption levels to the supplier or utility from each smart meter at short intervals has an advantage for the electricity supplier's planning and management purposes, it threatens user privacy by disclosing fine-grained consumption data and usage behavior to utility providers. In this study, we propose a distributed incremental data aggregation scheme where all smart meters on an aggregation path are involved in routing the data from the source meter to the collection unit. User privacy is preserved by symmetric homomorphic encryption, which allows smart meters to participate in the aggregation without seeing any intermediate or final result. Aggregated data is further integrated with an aggregate signature to achieve data integrity and smart meter authentication in such a way that dishonest or fake smart meters cannot falsify data en route. Only the collection unit can obtain the aggregated data and verify its integrity while the individual plain data are not exposed to the collection unit. Therefore, user privacy and security are improved for the smart metering in a smart grid network.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - Graduate School > Department of Computer Science and Engineering > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.