Proactive detection of cyber-physical grid attacks: A pre-attack phase identification and analysis using anomaly-based machine learning models

Cyber-physical power systems (CPPS), such as smart grids, are essential to modern infrastructure but are increasingly vulnerable to sophisticated cyber-attacks. Traditional security approaches often detect threats only after damage occurs, underscoring the need for proactive solutions. This research...

Full description

Saved in:

Bibliographic Details
Main Authors:	Shaharier Kabir, Nasif Hannan, Abu Shufian, Md Saniat Rahman Zishan
Format:	Article
Language:	English
Published:	Elsevier 2025-09-01
Series:	Array
Subjects:	Cyber-power physical systems Smart grid security Anomaly detection Machine learning Pre-attack phases Isolation forest
Online Access:	http://www.sciencedirect.com/science/article/pii/S2590005625000682
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!

Proactive detection of cyber-physical grid attacks: A pre-attack phase identification and analysis using anomaly-based machine learning models

Similar Items