Mehrdad Saif

Physics-Informed Neural Network for Detecting and Isolating Faults in Cooperative Adaptive Cruise Control

This paper presents a Physics-Informed Neural Network (PINN) framework for detecting and isolating sensor and communication faults in Cooperative Adaptive Cruise Control (CACC). Unlike conventional data-driven methods, the proposed approach integrates the platoon dynamics into the neural network training process, enabl...

FedNIA: Noise-Induced Activation Analysis for Mitigating Data Poisoning in Federated Learning

FedNIA injects random noise inputs to analyze the layerwise activation patterns in client models leveraging an autoencoder that detects abnormal behaviors indicative of data poisoning and can defend against diverse attack types, including sample poisoning, label flipping, and backdoors.

Design of Stealthy Deception Attacks on Remote Estimation With Historical Data