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Information Masking Theory for Data Protection in Future Cloud-Based Energy Management

Implementation of advanced information and communication technologies upgrades energy management systems (EMSs) by allowing more participants and improving the control ability, in which cloud-based service plays an essential role. However, its information exchange also raises concern about information safety and privacy. To overcome this challenge, we propose the mechanism of information masking (IM), which helps to hide the original information by transforming it to another form. In the main body, we first review the basic theory of IM. Then, we introduce three typical scenarios for cloud-based EMSs [i.e., home/building EMS (for end users), aggregated load/generation management (for aggregated loads), and coordinated dispatch (for multi-regional power systems)], then analyze and compare their IM requirements. After discussing the IM design rules for two general requirements, we discuss IM algorithms for the three scenarios and study three typical cases to verify the feasibility and effectiveness of the IM approaches. The results show that the proposed IM approaches successfully hide all the targeted information while leading to only minor increases in computation cost and matrix sparsity.