A Distributed Privacy-Preserving Integrity Verification Framework for the Smart Grid

Smart grid functionalities, such as real-time monitoring and load balancing, require smart metering data collection at frequent time intervals. There are several threats to this data collection process, including passive threats to customers' privacy and active threats to metering data integrity. Customer privacy can be breached with the fine grained metering data collection, and without appropriate measures for integrity verification, the metering data can be exploited to hamper the smart grid functionalities. Distributed privacy-preserving frameworks are more robust than centralized frameworks against privacy threats. Several distributed privacy-preserving frameworks for smart metering data exist in the literature. However, these frameworks assume a semi-honest threat model that does not consider threats to data integrity. This paper introduces a distributed framework under a malicious adversarial model. The proposed framework is capable of verifying metering data's integrity while maintaining customer privacy. We evaluate our framework's performance via simulation and show its feasibility for real-world deployments. We also evaluate the framework's resilience to active and passive attacks, followed by a comparative analysis with existing related frameworks in the literature.