15 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…
An AI-Based Supervisory Measurement Integrity Validation Layer for Cyber-Resilient AC/DC Protection in Inverter-Based Microgrids
Ahmad Mohammad Saber, Ahmed Saber Refae, Davor Svetinovic +4
Line current differential relays (LCDRs) are measurement-driven relays that rely on time-synchronized multi-phase current waveforms to infer internal faults in AC and DC power netw…
Dual-Stage LLM Framework for Scenario-Centric Semantic Interpretation in Driving Assistance
Jean Douglas Carvalho, Hugo Taciro Kenji, Ahmad Mohammad Saber +3
Advanced Driver Assistance Systems (ADAS) increasingly rely on learning-based perception, yet safety-relevant failures often arise without component malfunction, driven instead by…
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…
Multimodal Large Language Model Framework for Safe and Interpretable Grid-Integrated EVs
Jean Douglas Carvalho, Hugo Kenji, Ahmad Mohammad Saber +3
The integration of electric vehicles (EVs) into smart grids presents unique opportunities to enhance both transportation systems and energy networks. However, ensuring safe and int…