Document Type
Article
Publication Date
6-8-2023
Abstract
For the first time, commercial grade smart meters have been subjected to cyber security attacks to understand their operation and security resilience under different attack scenarios. Cyber security is a matter of top concern for utility companies installing smart meters for remote collection of power usage data from customer premises. Keeping power-usage data secure and to maintain system’s resiliency under cyber security attacks is very important. In Smart electric grids, the power usage data from smart meters are periodically reported to the utility company. Reporting and remote monitoring of power usage data requires the use of data network protocols, which introduces security vulnerabilities. Cyber security attacks can impact reporting mechanisms in the smart grid, which may result in alteration or complete loss of power usage data as reported to the utility company. Despite the wide deployment of smart meters, there has not been much experimental work done to evaluate resiliency and data integrity of smart meters under security attacks. It is not clear how the operation of smart meters or the remote collection of power-usage data can be affected under security attacks. In this paper, we present our experimental work to test security resiliency of the commercial grade smart meters. We conducted real experiments, using smart electric meters from leading manufacturers to investigate data integrity under common data security attacks in a lab environment using real network equipment. Based on the experimental observations, it was discovered that the common cybersecurity attacks were able to adversely impact the data reporting operation of the smart electric meters. Cybersecurity attacks in some cases were found to cause complete loss of reporting of the power-usage data to the remote monitoring station.
Recommended Citation
H. Kumar, O. A. Alvarez and S. Kumar, "Experimental Evaluation of Smart Electric Meters’ Resilience Under Cyber Security Attacks," in IEEE Access, vol. 11, pp. 55349-55360, 2023, doi: 10.1109/ACCESS.2023.3278738.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Publication Title
IEEE Access
DOI
https://doi.org/10.1109/ACCESS.2023.3278738
Comments
Under a Creative Commons License