Artificial Intelligence and Physics-Based Anomaly Detection in the Smart Grid: A Survey
The integration of advanced communication systems and distributed resources has transformed power systems, enhancing control and efficiency in the Smart Grid. However, this increased complexity introduces new vulnerabilities, heightening risks of cyber-attacks, equipment failures, and other anomalie...
Saved in:
Main Authors: | Giovanni Battista Gaggero, Paola Girdinio, Mario Marchese |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10858740/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
BESS-Set: A Dataset for Cybersecurity Monitoring in a Battery Energy Storage System
by: Giovanni Battista Gaggero, et al.
Published: (2024-01-01) -
Global Information and Structure Tensor Guided Collaborative Representation for Anomaly Detection
by: Meiping Song, et al.
Published: (2025-01-01) -
Driver anomaly detection in cargo terminal
by: Shahab Emaani, et al.
Published: (2025-01-01) -
Anomaly Detection in IoMT Environment Based on Machine Learning: An Overview
by: Peyman Vafadoost Sabzevar, et al.
Published: (2024-12-01) -
Machine Learning-Based Anomaly Prediction for Proactive Monitoring in Data Centers: A Case Study on INFN-CNAF
by: Andrea Asperti, et al.
Published: (2025-01-01)