Privacy-preserving and Efficient Aggregation based on Blockchain for Power Grid Communications in Smart Communities

TL;DR

This paper presents a blockchain-based privacy-preserving data aggregation scheme for smart grids, enhancing user privacy and efficiency in electricity consumption data collection within smart communities.

Contribution

It introduces a novel grouping and blockchain approach with pseudonyms and bloom filters to protect user privacy and improve data aggregation performance.

Findings

The scheme effectively preserves user privacy against data analysis attacks.

It outperforms existing methods in efficiency and security.

The approach is suitable for real-time smart grid applications.

Abstract

Intelligence is one of the most important aspects in the development of our future communities. Ranging from smart home, smart building, to smart city, all these smart infrastructures must be supported by intelligent power supply. Smart grid is proposed to solve all challenges of future electricity supply. In smart grid, in order to realize optimal scheduling, a Smart Meter (SM) is installed at each home to collect the near real-time electricity consumption data, which can be used by the utilities to offer better smart home services. However, the near real-time data may disclose user's privacy. An adversary may track the application usage patterns by analyzing the user's electricity consumption profile. In this paper, we propose a privacy-preserving and efficient data aggregation scheme. We divide users into different groups and each group has a private blockchain to record its members' data. To preserve the inner privacy within a group, we use pseudonym to hide user's identity, and each user may create multiple pseudonyms and associate his/her data with different pseudonyms. In addition, the bloom filter is adopted for fast authentication. The analysis shows that the proposed scheme can meet the security requirements, and achieve a better performance than other popular methods.