A Hybrid Machine Learning-Based Framework for Data Injection Attack Detection in Smart Grids Using PCA and Stacked Autoencoders Article

Tufail, Shahid, Iqbal, Hasan, Tariq, Mohd et al. (2025). A Hybrid Machine Learning-Based Framework for Data Injection Attack Detection in Smart Grids Using PCA and Stacked Autoencoders . IEEE ACCESS, 13 33783-33798. 10.1109/ACCESS.2025.3543751

cited authors

  • Tufail, Shahid; Iqbal, Hasan; Tariq, Mohd; Sarwat, Arif I

authors

publication date

  • January 1, 2025

published in

keywords

  • Accuracy
  • Autoencoders
  • CYBER-SECURITY
  • Computer Science
  • Computer Science, Information Systems
  • Computer security
  • Data models
  • Dimensionality reduction
  • Engineering
  • Engineering, Electrical & Electronic
  • INTRUSION DETECTION
  • Machine learning algorithms
  • Photovoltaic (PV) systems
  • Principal component analysis
  • Random forests
  • Science & Technology
  • Smart grids
  • Support vector machines
  • Technology
  • Telecommunications
  • autoencoders
  • grid-connected PV systems
  • machine learning algorithms
  • multi-layer perceptron (MLP)
  • principal component analysis (PCA)
  • random forest

Digital Object Identifier (DOI)

publisher

  • IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

start page

  • 33783

end page

  • 33798

volume

  • 13