Fine-Tuned RNN-Based Detector for Electricity Theft Attacks in Smart Grid Generation Domain

Fine-Tuned RNN-Based Detector for Electricity Theft Attacks in Smart Grid Generation Domain

<p dir="ltr">In this article, we investigate the problem of electricity theft attacks on smart meters when malicious customers (i.e., adversaries) claim injecting more generated energy into the grid to get more profits from utility companies. These attacks can be applied by accessing...

Full description

Saved in:
Bibliographic Details
Main Author: Maymouna Ez Eddin (16904604) (author)
Other Authors: Abdullatif Albaseer (16904607) (author), Mohamed Abdallah (3073191) (author), Sertac Bayhan (16388511) (author), Marwa K. Qaraqe (8115020) (author), Saif Al-Kuwari (16904610) (author), Haitham Abu-Rub (16855500) (author)
Published: 2022
Subjects:
Engineering
Communications engineering
Electrical engineering
Information and computing sciences
Cybersecurity and privacy
Machine learning
Detectors
Smart meters
Anomaly detection
Perturbation methods
Meters
Fuels
Renewable energy sources
Smart grids
Deep learning
Cyberattacks on smart grid
Electricity theft
Generation domain
Deep-learning (DL)-based detector
Small perturbations
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items