6 papers
Evaluating Jailbreaking Vulnerabilities in LLMs Deployed as Assistants for Smart Grid Operations: A Benchmark Against NERC Standards
Taha Hammadia, Lucas Rea, Ahmad Mohammad Saber +2
The deployment of Large Language Models (LLMs) as assistants in electric grid operations promises to streamline compliance and decision-making but exposes new vulnerabilities to pr…
Large Language Models as Explainable Cyberattack Detectors for Energy Industrial Control Systems
Weiyi Kong, Ahmad Mohammad Saber, Amr Youssef +1
In modern energy systems, industrial control systems (ICS) and power-system SCADA require intrusion detection that is not only accurate but also auditable by operators. The ICS int…
Large Language Models for Detecting Cyberattacks on Smart Grid Protective Relays
Ahmad Mohammad Saber, Saeed Jafari, Zhengmao Ouyang +3
This paper presents a large language model (LLM)-based framework that adapts and fine-tunes compact LLMs for detecting cyberattacks on transformer current differential relays (TCDR…
A Kolmogorov-Arnold Network for Interpretable Cyberattack Detection in AGC Systems
Jehad Jilan, Niranjana Naveen Nambiar, Ahmad Mohammad Saber +3
Automatic Generation Control (AGC) is essential for power grid stability but remains vulnerable to stealthy cyberattacks, such as False Data Injection Attacks (FDIAs), which can di…
Large Language Model-Based Framework for Explainable Cyberattack Detection in Automatic Generation Control Systems
Muhammad Sharshar, Ahmad Mohammad Saber, Davor Svetinovic +3
The increasing digitization of smart grids has improved operational efficiency but also introduced new cybersecurity vulnerabilities, such as False Data Injection Attacks (FDIAs) t…
A Kolmogorov-Arnold Network for Explainable Detection of Cyberattacks on EV Chargers
Ahmad Mohammad Saber, Max Mauro Dias Santos, Mohammad Al Janaideh +2
The increasing adoption of Electric Vehicles (EVs) and the expansion of charging infrastructure and their reliance on communication expose Electric Vehicle Supply Equipment (EVSE)…