Privacy-Preserving Hierarchical State Estimation in Untrustworthy Cloud Environments

被引:10
作者
Wang, Jingyu [1 ,2 ]
Shi, Dongyuan [1 ,2 ]
Chen, Jinfu [1 ,2 ]
Liu, Chen-Ching [3 ]
机构
[1] Huazhong Univ Sci & Technol, Hubei Elect Power Secur & High Efficiency Key Lab, State Key Lab Adv Electromagnet Engn & Technol, Wuhan 430074, Peoples R China
[2] Huazhong Univ Sci & Technol, Sch Elect & Elect Engn, Wuhan 430074, Peoples R China
[3] Virginia Polytech Inst & State Univ, Bradley Dept Elect & Comp Engn, Blacksburg, VA 24061 USA
基金
中国国家自然科学基金; 美国国家科学基金会;
关键词
Power systems; State estimation; Privacy; Encryption; Servers; Cloud computing; hierarchical state estimation; privacy preservation; thresholded Paillier cryptosystem; untrustworthy environment;
D O I
10.1109/TSG.2020.3023891
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页码:1541 / 1551
页数:11
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