Visible to the public Stealthy Attack Detection for Privacy-preserving Real-time Pricing in Smart Grids

TitleStealthy Attack Detection for Privacy-preserving Real-time Pricing in Smart Grids
Publication TypeConference Paper
Year of Publication2022
AuthorsWu, Fazong, Wang, Xin, Yang, Ming, Zhang, Heng, Wu, Xiaoming, Yu, Jia
Conference Name2022 13th Asian Control Conference (ASCC)
Keywordsattack detection, Collaboration, demand side management, Differential privacy, Policy Based Governance, Pricing, privacy, pubcrawl, real-time pricing, Real-time Systems, Robustness, Smart grid, smart grid consumer privacy, Uncertainty
Abstract

Over the past decade, smart grids have been widely implemented. Real-time pricing can better address demand-side management in smart grids. Real-time pricing requires managers to interact more with consumers at the data level, which raises many privacy threats. Thus, we introduce differential privacy into the Real-time pricing for privacy protection. However, differential privacy leaves more space for an adversary to compromise the robustness of the system, which has not been well addressed in the literature. In this paper, we propose a novel active attack detection scheme against stealthy attacks, and then give the proof of correctness and effectiveness of the proposed scheme. Further, we conduct extensive experiments with real datasets from CER to verify the detection performance of the proposed scheme.

DOI10.23919/ASCC56756.2022.9828256
Citation Keywu_stealthy_2022