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CORRECTION article

Front. Energy Res., 26 June 2024
Sec. Smart Grids
Volume 12 - 2024 | https://doi.org/10.3389/fenrg.2024.1433901

Corrigendum: A data-driven ensemble technique for the detection of false data injection attacks in the smart grid framework

This article is a correction to:

  1. A data-driven ensemble technique for the detection of false data injection attacks in the smart grid framework

    1. Read original article
Tania Gupta Tania Gupta1*Richa BhatiaRicha Bhatia2Sachin SharmaSachin Sharma3Ch. Rami Reddy, Ch. Rami Reddy4,5*Kareem M. AboRasKareem M. AboRas6Wael Mobarak Wael Mobarak7*
  • 1Department of Electronics and Communication, NSUT East Campus (Affiliated to GGSIPU), Delhi, India
  • 2Netaji Subhash University of Technology, Delhi, India
  • 3Electrical Engineering Department, Graphic Era Deemed to be University, Dehradun, India
  • 4Department of Electrical and Electronics Engineering, Joginpally B. R. Engineering College, Hyderabad, India
  • 5Applied Science Research Center, Applied Science Private University, Amman, Jordan
  • 6Department of Electrical Power and Machines, Faculty of Engineering, Alexandria University, Alexandria, Egypt
  • 7College of Engineering, University of Business and Technology, Jeddah, Saudi Arabia

A Corrigendum on
A data-driven ensemble technique for the detection of false data injection attacks in the smart grid framework

by Gupta T, Bhatia R, Sharma S, Reddy CR, AboRas KM and Mobarak W (2024). Front. Energy Res. 12:1366465. doi: 10.3389/fenrg.2024.1366465

In the published article, there was an error in Affiliation 7. Instead of “Electrical Engineering Department, University of Business and Technology, Jeddah, Saudi Arabia,” it should be “College of Engineering, University of Business and Technology, Jeddah, Saudi Arabia.”

Also, we would like to remove the affiliation no. 8.

The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Keywords: advanced metering infrastructure, cyber security, false data injection attacks, feature extraction, machine learning, smart meter

Citation: Gupta T, Bhatia R, Sharma S, Rami Reddy C, AboRas KM and Mobarak W (2024) Corrigendum: A data-driven ensemble technique for the detection of false data injection attacks in the smart grid framework. Front. Energy Res. 12:1433901. doi: 10.3389/fenrg.2024.1433901

Received: 16 May 2024; Accepted: 13 June 2024;
Published: 26 June 2024.

Approved by:

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2024 Gupta, Bhatia, Sharma, Rami Reddy, AboRas and Mobarak. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Tania Gupta, taniagupta2409@gmail.com; Ch. Rami Reddy, crreddy229@gmail.com; Wael Mobarak, w.fawzy@ubt.edu.sa

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.