Title
Privacy-Preserving Hierarchical State Estimation in Untrustworthy Cloud Environments
Abstract
Hierarchical state estimation (HSE) is often deployed to evaluate the states of an interconnected power system from telemetered measurements. By HSE, each low-level control center (LCC) takes charge of the estimation of its internal states, whereas a trusted high-level control center (HCC) assumes the coordination of boundary states. However, a trusted HCC may not always exist in practice; a cloud server can take the role of an HCC in case no such facility is available. Since it is prohibited to release sensitive power grid data to untrustworthy cloud environments, considerations need to be given to avoid breaches of LCCs' privacy when outsourcing the coordination tasks to the cloud server. To this end, this article proposes a privacy-preserving HSE framework, which rearranges the regular HSE procedure to integrate a degree-2 variant of the Thresholded Paillier Cryptosystem (D2TPC). Attributed to D2TPC, computations by the cloud-based HCC can be conducted entirely in the ciphertext space. Even if the HCC and some LCCs conspire together to share the information they have, the privacy of non-conspiring LCCs is still assured. Experiments on various scales of test systems demonstrate a high level of accuracy, efficiency, and scalability of the proposed framework.
Year
DOI
Venue
2021
10.1109/TSG.2020.3023891
IEEE Transactions on Smart Grid
Keywords
DocType
Volume
Cloud computing,hierarchical state estimation,privacy preservation,thresholded Paillier cryptosystem,untrustworthy environment
Journal
12
Issue
ISSN
Citations 
2
1949-3053
1
PageRank 
References 
Authors
0.36
0
4
Name
Order
Citations
PageRank
J. Wang147995.23
Dong-Yuan Shi2395.52
Jinfu Chen38011.62
Chen-Ching Liu47912.39