5 papers
LoRA-Diffusion: Parameter-Efficient Fine-Tuning via Low-Rank Trajectory Decomposition
Iman Khazrak, Narges Nejad, Mohammadhossein Homaei +2
Parameter-efficient fine-tuning methods such as LoRA have transformed the adaptation of large autoregressive language models, enabling task-specific customization with substantiall…
Cyber-Resilient Digital Twins: Discriminating Attacks for Safe Critical Infrastructure Control
Mohammadhossein Homaei, Iman Khazrak, Rubén Molano +2
Industrial Cyber-Physical Systems (ICPS) face growing threats from cyber-attacks that exploit sensor and control vulnerabilities. Digital Twin (DT) technology can detect anomalies…
Information-Theoretic Digital Twins for Stealthy Attack Detection in Industrial Control Systems: A Closed-Form KL Divergence Approach
Inda Kreso, Mehran Tarif, Fatemeh Moradi +3
Digital twins (DTs) are increasingly used to monitor and secure Industrial Control Systems (ICS), yet detecting stealthy False Data Injection Attacks (FDIAs) that manipulate system…
Graph Attention Networks with Physical Constraints for Anomaly Detection
Mohammadhossein Homaei, Iman Khazrak, Ruben Molano +2
Water distribution systems (WDSs) face increasing cyber-physical risks, which make reliable anomaly detection essential. Many data-driven models ignore network topology and are har…
Addressing Small and Imbalanced Medical Image Datasets Using Generative Models: A Comparative Study of DDPM and PGGANs with Random and Greedy K Sampling
Iman Khazrak, Shakhnoza Takhirova, Mostafa M. Rezaee +3
The development of accurate medical image classification models is often constrained by privacy concerns and data scarcity for certain conditions, leading to small and imbalanced d…