Xuebin Ren, Xinyu Yang, Jie Lin, Qingyu Yang, Wei Yu
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On Scaling Perturbation Based Privacy-Preserving Schemes in Smart Metering Systems
The smart grid poses great concern about the exposure of consumers' privacy as the fine-grained measurements in the smart metering system can expose consumer's privacy through the disclosure of accurate load profiles of home energy usage. To address this issue, in this paper we propose novel scaling perturbation based privacy-preserving schemes that can achieve great utility for fine-grained measurements in a privacy-friendly and cost-effective manner. Our schemes adopt the measurement-based scaling perturbation to hide original measurements with low cost. Through a combination of both extensive theoretical analysis and experiments, our results show that the proposed schemes can preserve consumers' privacy through fine-grained measurements and achieve a better utility-privacy tradeoff in comparison with the existing schemes.