An efficient data aggregation scheme for privacy-friendly dynamic pricing-based billing and demand-response management in smart grids

Gope, Prosanta; Sikdar, Biplab

Abstract

Smart grids take advantage of information and communication technologies to achieve energy efficiency, automation and reliability. These systems allow two-way communications and power flow between the grid and consumers. However, these bidirectional communications introduce several security and privacy threats to consumers. One of the open challenges in this context is user privacy when smart meters are used to capture fine-grained energy usage information. Although considerable research has been carried out in this direction, most of the existing solutions invariably introduce computational complexity and overhead, which makes them infeasible for resource constrained smart meters. In this paper, we propose a privacy-friendly and efficient data aggregation scheme (EDAS) for dynamic pricing based billing and demand-response management in smart grids. To the best of our knowledge, this is the first paper to address privacy in the context of billing under dynamic electricity pricing. Security and performance analyses show that the proposed scheme offers better privacy protection for electric meter reading aggregation and computational efficiency, as compared to existing schemes.

Citation

Gope, P., & Sikdar, B. (2018). An efficient data aggregation scheme for privacy-friendly dynamic pricing-based billing and demand-response management in smart grids. IEEE internet of things journal, 5(4), 3126-3135. https://doi.org/10.1109/JIOT.2018.2833863

• Journal Article Type: Article
• Acceptance Date: Apr 30, 2018
• Online Publication Date: May 8, 2018
• Publication Date: Aug 1, 2018
• Deposit Date: Jul 2, 2018
• Publicly Available Date: Jul 3, 2018
• Journal: IEEE Internet of Things Journal
• Print ISSN: 2327-4662
• Electronic ISSN: 2327-4662
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 5
• Issue: 4
• Pages: 3126-3135
• DOI: https://doi.org/10.1109/JIOT.2018.2833863
• Keywords: Data aggregation; Privacy; Smart grids
• Public URL: https://hull-repository.worktribe.com/output/906109
• Publisher URL: https://ieeexplore.ieee.org/document/8356024/