22 papers
Attention in Motion: Secure Platooning via Transformer-based Misbehavior Detection
Konstantinos Kalogiannis, Ahmed Mohamed Hussain, Hexu Li +1
Vehicular platooning promises transformative improvements in transportation efficiency and safety through the coordination of multi-vehicle formations enabled by Vehicle-to-Everyth…
Protecting Cryptographic Libraries against Side-Channel and Code-Reuse Attacks
Rodothea Myrsini Tsoupidi, Elena Troubitsyna, Panos Papadimitratos
Cryptographic libraries, an essential part of cybersecurity, are shown to be susceptible to different types of attacks, including side-channel and memory-corruption attacks. In thi…
PAMPOS: Causal Transformer-based Trajectory Prediction for Attack-Agnostic Misbehavior Detection in V2X Networks
Konstantinos Kalogiannis, Ahmed Mohamed Hussain, Panos Papadimitratos
Misbehavior detection in Vehicle-to-Everything (V2X) networks is a second line of defense against insider falsification attacks that cryptographic mechanisms alone cannot address.…
Beyond Context: Large Language Models' Failure to Grasp Users' Intent
Ahmed M. Hussain, Salahuddin Salahuddin
Current Large Language Models (LLMs) safety approaches focus on explicitly harmful content while overlooking a critical vulnerability: the inability to understand context and recog…
FedTrident: Resilient Road Condition Classification Against Poisoning Attacks in Federated Learning
Sheng Liu, Panos Papadimitratos
FL has emerged as a transformative paradigm for ITS, notably camera-based Road Condition Classification (RCC). However, by enabling collaboration, FL-based RCC exposes the system t…
DEFEND: Poisoned Model Detection and Malicious Client Exclusion Mechanism for Secure Federated Learning-based Road Condition Classification
Sheng Liu, Panos Papadimitratos
Federated Learning (FL) has drawn the attention of the Intelligent Transportation Systems (ITS) community. FL can train various models for ITS tasks, notably camera-based Road Cond…