21 citations · 42 across the 14 of their papers we have counts for
10 papers · 1 filter
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.…
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…
AttentionGuard: Transformer-based Misbehavior Detection for Secure Vehicular Platoons
Hexu Li, Konstantinos Kalogiannis, Ahmed Mohamed Hussain +1
Vehicle platooning, with vehicles traveling in close formation coordinated through Vehicle-to-Everything (V2X) communications, offers significant benefits in fuel efficiency and ro…
Privacy-Preserving Secure Neighbor Discovery for Wireless Networks
Ahmed Mohamed Hussain, Panos Papadimitratos
Traditional Neighbor Discovery (ND) and Secure Neighbor Discovery (SND) are key elements for network functionality. SND is a hard problem, satisfying not only typical security prop…
Prompt, Divide, and Conquer: Bypassing Large Language Model Safety Filters via Segmented and Distributed Prompt Processing
Johan Wahréus, Ahmed Hussain, Panos Papadimitratos
Large Language Models (LLMs) have transformed task automation and content generation across various domains while incorporating safety filters to prevent misuse. We introduce a nov…
LLMs Have Rhythm: Fingerprinting Large Language Models Using Inter-Token Times and Network Traffic Analysis
Saeif Alhazbi, Ahmed Mohamed Hussain, Gabriele Oligeri +1
As Large Language Models (LLMs) become increasingly integrated into many technological ecosystems across various domains and industries, identifying which model is deployed or bein…
CySecBench: Generative AI-based CyberSecurity-focused Prompt Dataset for Benchmarking Large Language Models
Johan Wahréus, Ahmed Mohamed Hussain, Panos Papadimitratos
Numerous studies have investigated methods for jailbreaking Large Language Models (LLMs) to generate harmful content. Typically, these methods are evaluated using datasets of malic…
Radio Frequency Fingerprinting via Deep Learning: Challenges and Opportunities
Saeif Al-Hazbi, Ahmed Hussain, Savio Sciancalepore +2
Radio Frequency Fingerprinting (RFF) techniques promise to authenticate wireless devices at the physical layer based on inherent hardware imperfections introduced during manufactur…
The Dark (and Bright) Side of IoT: Attacks and Countermeasures for Identifying Smart Home Devices and Services
Ahmed Mohamed Hussain, Gabriele Oligeri, Thiemo Voigt
We present a new machine learning-based attack that exploits network patterns to detect the presence of smart IoT devices and running services in the WiFi radio spectrum. We perfor…