Lightweight and privacy-friendly spatial data aggregation for secure power supply and demand management in smart grids

Gope, Prosanta; Sikdar, Biplab

Abstract

The concept of smart metering allows real-time measurement of power demand which in turn is expected to result in more efficient energy use and better load balancing. However, finely granular measurements reported by smart meters can lead to starkly increased exposure of sensitive information, including various personal attributes and activities. Even though several security solutions have been proposed in recent years to address this issue, most of the existing solutions are based on publickey cryptographic primitives such as homomorphic encryption, elliptic curve digital signature algorithms (ECDSA), etc. which are ill-suited for the resource constrained smart meters. On the other hand, to address the computational inefficiency issue, some masking-based solutions have been proposed. However, these schemes cannot ensure some of the imperative security properties such as consumer’s privacy, sender authentication, etc. In this paper, we first propose a lightweight and privacyfriendly masking-based spatial data aggregation scheme for secure forecasting of power demand in smart grids. Our scheme only uses lightweight cryptographic primitives such as hash functions, exclusive-OR operations, etc. Subsequently, we propose a secure billing solution for smart grids. As compared to existing solutions, our scheme is simple and can ensure better privacy protection and computational efficiency, which are essential for smart grids.

Citation

Gope, P., & Sikdar, B. (2019). Lightweight and privacy-friendly spatial data aggregation for secure power supply and demand management in smart grids. IEEE transactions on information forensics and security, 14(6), 1554 - 1566. https://doi.org/10.1109/TIFS.2018.2881730

• Journal Article Type: Article
• Acceptance Date: Oct 27, 2018
• Online Publication Date: Nov 16, 2018
• Publication Date: 2019-06
• Deposit Date: Nov 23, 2018
• Publicly Available Date: Nov 23, 2018
• Journal: IEEE Transactions on Information Forensics and Security
• Print ISSN: 1556-6013
• Electronic ISSN: 1556-6021
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 14
• Issue: 6
• Pages: 1554 - 1566
• DOI: https://doi.org/10.1109/TIFS.2018.2881730
• Keywords: Computer Networks and Communications; Safety, Risk, Reliability and Quality
• Public URL: https://hull-repository.worktribe.com/output/1160140
• Publisher URL: https://ieeexplore.ieee.org/document/8537927