A Distributed Privacy-Preserving Framework With Integrity Verification Capabilities for Metering Data and Dynamic Billing in a Malicious Setting

Smart metering enables near-real time collection of customer energy consumption data by Electrical Service Providers (ESP). Access to this granular metering data raises privacy concerns, hindering global adoption of the smart grid. Aggregation-based frameworks aim to address these concerns, but suffer from several limitations such as, a high computational overhead on smart meters, architectural complexity, and vulnerability to single points of compromise. Distributed aggregation-based frameworks show promise, but often assume an unrealistic semi-honest threat model, a lack of integrity verification capabilities for metering data, and dynamic billing (Time Of Use) capabilities. This paper introduces a distributed framework in a malicious setting that provides integrity verification of metering data while preserving customer privacy. To the best of our knowledge, the proposed framework is the first attempt to include integrity verification capabilities of metering data and dynamic billing in a distributed data collection setting while considering a malicious adversary. A proof of concept demonstrates our proposed framework’s viability and performance against other frameworks. Our framework is shown to be lightweight on smart meters, resilient to cyberattacks, and more efficient, compared to competing techniques in the literature.