21 citations · 42 across the 14 of their papers we have counts for
14 papers
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…
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…
Jailbreaking Large Language Models Through Content Concretization
Johan Wahréus, Ahmed Hussain, Panos Papadimitratos
Large Language Models (LLMs) are increasingly deployed for task automation and content generation, yet their safety mechanisms remain vulnerable to circumvention through different…
NEFMind: Parameter-Efficient Fine-Tuning of Open-Source LLMs for Telecom APIs Automation
Zainab Khan, Ahmed Hussain, Mukesh Thakur +2
The use of Service-Based Architecture in modern telecommunications has exponentially increased Network Functions (NFs) and Application Programming Interfaces (APIs), creating subst…
Less Data, More Security: Advancing Cybersecurity LLMs Specialization via Resource-Efficient Domain-Adaptive Continuous Pre-training with Minimal Tokens
Salahuddin Salahuddin, Ahmed Hussain, Jussi Löppönen +1
The increasing scale of AI workloads demands High-Performance Computing (HPC) infrastructure and training methodologies that are both scalable and sustainable. While Large Language…