Privacy-Preserving Power Usage and Supply Control in Smart Grid
Abstract
In a cyber-physical system, the control component plays an essential role to make the cyber and physical components work harmoniously together. When information collected from the physical space contains private or sensitive data that cannot be passed onto the cyber space, properly controlling the cyber-physical system becomes a very challenging task. For instance, the smart grid systems, a replacement for the traditional power grid systems, have been widely used in the industries. To prevent power shortage, threshold-based power usage control (PUC) in a smart grid considers a situation where the utility company sets a threshold to control the total power usage or supply of a neighborhood. If the total power usage exceeds the threshold, either certain households need to reduce their power consumption or the utility company needs to buy additional power supplies to meet the increasing demand. In these scenarios, the utility company needs to frequently collect power usage data from smart meters. It has been well documented that these power usage data can reveal a person's daily activity and violate personal privacy. To mitigate the privacy concerns, the goal of this paper is to develop efficient and privacy-preserving power usage control protocols that allow a utility company to balance supply and demand in a smart grid without violating personal privacy of its customers. We will provide extensive empirical study to show the practicality of our proposed protocols.
Recommended Citation
H. Chun et al., "Privacy-Preserving Power Usage and Supply Control in Smart Grid," Computers and Security, vol. 77, pp. 709 - 719, Elsevier, Aug 2018.
The definitive version is available at https://doi.org/10.1016/j.cose.2018.01.021
Department(s)
Computer Science
Keywords and Phrases
Control; Power usage; Privacy-preserving; Smart grid; Supply
International Standard Serial Number (ISSN)
0167-4048
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Elsevier, All rights reserved.
Publication Date
01 Aug 2018