Protecting User Privacy Based on Secret Sharing with Error Tolerance for Big Data in Smart Grid
This addresses privacy concerns for users in smart grid applications, but it appears incremental as it builds on existing secret sharing and differential privacy techniques.
The paper tackles the problem of user privacy in smart data aggregation for smart grids by proposing a scheme based on secret sharing with error tolerance, ensuring the control center receives integrated data without revealing sensitive information, and validates this through security analysis and experiments.
In smart grid, large quantities of data is collected from various applications, such as smart metering substation state monitoring, electric energy data acquisition, and smart home. Big data acquired in smart grid applications usually is sensitive. For instance, in order to dispatch accurately and support the dynamic price, lots of smart meters are installed at user's house to collect the real-time data, but all these collected data are related to user privacy. In this paper, we propose a data aggregation scheme based on secret sharing with error tolerance in smart grid, which ensures that the control center gets the integrated data without revealing users' privacy. Meanwhile, we also consider the differential privacy and error tolerance during the data aggregation. At last, we analyze the security of our scheme and carry out experiments to validate the results.