Paper Info
Title
Blockchain and homomorphic encryption-based privacy-preserving data aggregation model in smart grid
Abstract
AbstractAbstractIn recent years, rapid advancements in smart grid technology and smart metering systems have raised serious privacy concerns about the collection of customers’ real-time energy usage behaviors. Due to cybersecurity attacks and threats, data aggregation operations in a smart grid are challenging. The majority of existing techniques have high computation and communication costs and are still vulnerable to various security and privacy concerns. This paper proposes a deep learning and homomorphic encryption-based privacy-preserving data aggregation model to mitigate the negative impact of a flash workload on the accuracy of prediction models. The model also ensures a secure data aggregation process with low computational overhead. The proposed model is 80% more effective than the traditional approach in detecting smart meter manipulation, and the computation cost is 20% to 80% less than existing techniques. Thus, the proposed blockchain and homomorphic encryption-based data aggregation (BHDA) scheme shows a significant improvement in performance and privacy preservation with minimal computation overhead for data aggregation in smart grids.Highlights •A homomorphic encryption-based data aggregation model for the smart grid system.•A blockchain-based data aggregation framework to enhance security in a smart grid system.•The framework reduces the computation to work with smart meters with low computation power.•The computation cost of the model is 20% to 80% less as compared to existing techniques.
Year
DOI
Venue
2021
10.1016/j.compeleceng.2021.107209
Periodicals
Keywords
DocType
Volume
Smart grid, Data aggregation, Homomorphic encryption, Blockchain, Privacy preservation
Journal
93
Issue
ISSN
Citations 
C
0045-7906
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Parminder Singh100.34
Mehedi Masud27726.95
M. Shamim Hossain300.34
Avinash Kaur464.14