Protecting User Privacy Based on Secret Sharing with Error Tolerance for Big Data in Smart Grid

TL;DR

This paper introduces a privacy-preserving data aggregation scheme for smart grids using secret sharing with error tolerance, ensuring user privacy while maintaining data accuracy and security.

Contribution

It proposes a novel secret sharing-based data aggregation method with error tolerance and differential privacy considerations for smart grid applications.

Findings

The scheme effectively protects user privacy during data aggregation.

Experimental results validate the scheme's accuracy and security.

The method supports error tolerance in big data collection for smart grids.

Abstract

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.