Privacy Preserving Smart Meter Streaming Against Information Leakage of Appliance Status

Abstract

The smart grid frequently collects consumers' fine-grained power usage data through smart meters to facilitate various applications, such as billing, load monitoring, regional statistics, and demand response. However, the smart meter reading streams may also pose severe privacy threats to the consumers by leaking their appliances' ON/OFF status. In this paper, we first quantitatively measure the information leakage with respect to specific appliances' status from any reading stream, and define a novel privacy notion to bound such information leakage. In addition, we propose a privacy preserving streaming algorithm with different options to effectively convert readings and promptly stream safe readings in different fashions. The output time series readings satisfy our privacy notion while guaranteeing excellent utility, such as extremely low aggregation errors and billing errors. Finally, we experimentally validate the effectiveness and efficiency of our approach using real data sets.