Zhong Fan
DEP2SA: A Decentralized Efficient Privacy-Preserving and Selective Aggregation Scheme in Advanced Metering Infrastructure
Fan, Zhong
Authors
Abstract
This paper proposes a novel solution, called a decentralized, efficient, privacy-preserving, and selective aggregation (DEP2SA) scheme, designed to support secure and user privacy-preserving data collection in the advanced metering infrastructure. DEP2SA is more efficient and applicable in real-life deployment, as compared with the state of the art, by adopting and adapting a number of key technologies: 1) it uses a multi-recipient system model, making it more applicable to a liberalized electricity market; 2) it uses the homomorphic Paillier encryption and selective aggregation methods to protect users' consumption data against both external and internal attacks, thus making it more secure; 3) it aggregates data at the gateways that are closest to the data originator, thus saving bandwidth and reducing the risk of creating a performance bottleneck in the system; and 4) it uses short signature and batch signature verification methods to further reduce computational and communication overheads imposed on aggregating nodes. The scheme has been analyzed in terms of security, computational, and communication overheads, and the results show that it is more secure, efficient, and scalable than related schemes.
Journal Article Type | Article |
---|---|
Acceptance Date | Dec 7, 2015 |
Online Publication Date | Dec 7, 2015 |
Publication Date | 2015 |
Publicly Available Date | Mar 28, 2024 |
Journal | IEEE ACCESS |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Volume | 3 |
Pages | 2828-2846 |
DOI | https://doi.org/10.1109/ACCESS.2015.2506198 |
Keywords | Smart grid, AMI, security, homomorphic encryption, privacy preserving, selective aggregation, data leakage |
Publisher URL | http://ieeexplore.ieee.org/document/7348648/ |
Files
Z Fan - DEP2SA.pdf
(14.6 Mb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
You might also like
The role of ‘living laboratories’ in accelerating the energy system decarbonization
(2022)
Journal Article
Data-driven battery operation for energy arbitrage using rainbow deep reinforcement learning
(2022)
Journal Article
Privacy Preserving Demand Forecasting to Encourage Consumer Acceptance of Smart Energy Meters
(2021)
Presentation / Conference
Downloadable Citations
About Keele Repository
Administrator e-mail: research.openaccess@keele.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search