Abstract
In this article, we analyze the inherent characteristics of smart grids, and point out that some electricity consumption data are very sensitive and should be encrypted. However, once the corresponding private key is compromised, the content of encrypted data would be leaked, thereby violating users' privacy. Additionally, since a control center (CC) is always required to conduct accurate statistic analysis on these data for subsequent services, it is highly demanded for CC to check the integrity of encrypted data. To this end, based on a modified Boneh-Goh-Nissim (BGN) cryptosystem, we propose a key-leakage resilient encrypted data aggregation (KLR-EDA) scheme with lightweight verification in fog-assisted smart grids. KLR-EDA enables each fog node to aggregate first-level verifiable encrypted data from smart meters in the same grid area, and forward them to the cloud server (CS) for long-term storage. Upon receiving flexible challenging list of fog nodes from CC, CS produces second-level verifiable encrypted aggregated data and returns the results to CC. KLR-EDA enables CC to check the integrity of encrypted aggregated data efficiently, and further obtain the statistic analysis results on the aggregated data without learning any information of individual user. In particular, even the private key of CC is exposed or compromised, any adversary cannot break users' privacy. We provide security analysis of KLR-EDA, and conduct performance evaluation to demonstrate its lightweight statistical analysis and verification advantages on the CC side.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.