168 citations · 330 across the 6 of their papers we have counts for
6 papers
Infinite Impulse Response Graph Neural Networks for Cyberattack Localization in Smart Grids
Osman Boyaci, M. Rasoul Narimani, Katherine Davis +1
This study employs Infinite Impulse Response (IIR) Graph Neural Networks (GNN) to efficiently model the inherent graph network structure of the smart grid data to address the cyber…
Spatio-Temporal Failure Propagation in Cyber-Physical Power Systems
Osman Boyaci, M. Rasoul Narimani, Katherine Davis +1
Cascading failure in power systems is triggered by a small perturbation that leads to a sequence of failures spread through the system. The interconnection between different compon…
Generating Connected, Simple, and Realistic Cyber Graphs for Smart Grids
Osman Boyaci, M. Rasoul Narimani, Katherine Davis +1
Smart grids integrate communication systems with power networks to enable power grids operation and command through real-time data collection and control signals. Designing, analyz…
Cyberattack Detection in Large-Scale Smart Grids using Chebyshev Graph Convolutional Networks
Osman Boyaci, Mohammad Rasoul Narimani, Katherine Davis +1
As a highly complex and integrated cyber-physical system, modern power grids are exposed to cyberattacks. False data injection attacks (FDIAs), specifically, represent a major clas…
Joint Detection and Localization of Stealth False Data Injection Attacks in Smart Grids using Graph Neural Networks
Osman Boyaci, Mohammad Rasoul Narimani, Katherine Davis +3
False data injection attacks (FDIA) are a main category of cyber-attacks threatening the security of power systems. Contrary to the detection of these attacks, less attention has b…
Graph Neural Networks Based Detection of Stealth False Data Injection Attacks in Smart Grids
Osman Boyaci, Amarachi Umunnakwe, Abhijeet Sahu +4
False data injection attacks (FDIAs) represent a major class of attacks that aim to break the integrity of measurements by injecting false data into the smart metering devices in p…