Perturbation-Based Schemes with Ultra-Lightweight Computation to Protect User Privacy in Smart Grid

Abstract

In smart grid, smart meters are deployed to collect power consumption data periodically, and the data are analyzed to improve the efficiency of power transmission and distribution. The collected consumption data may leak the usage patterns of domestic appliances, so that it may damage the behavior privacy of customers. Most related work to protect data privacy in smart grid relies on cryptographic primitives, for example, encryption, which induces a large amount of power consumption overhead. In this paper, we make the first attempt to propose solutions without any cryptographic computation to protect user privacy. The privacy in smart grid is formally defined in the paper. Three schemes are proposed: random perturbation scheme (RPS), random walk scheme (RWS), and distance-bounded random walk with perturbation scheme (DBS). Three algorithms are also proposed in each scheme, respectively. All schemes are ultra-lightweight in terms of computation without relying any cryptographic primitive. The privacy, soundness, and accuracy of proposed schemes are guaranteed and justified by strict analysis.