65 citations · 65 across the 7 of their papers we have counts for
7 papers
FlyTrap: Physical Distance-Pulling Attack Towards Camera-based Autonomous Target Tracking Systems
Shaoyuan Xie, Mohamad Habib Fakih, Junchi Lu +6
Autonomous Target Tracking (ATT) systems, especially ATT drones, are widely used in applications such as surveillance, border control, and law enforcement, while also being misused…
Invisible Ears at Your Fingertips: Acoustic Eavesdropping via Mouse Sensors
Mohamad Fakih, Rahul Dharmaji, Youssef Mahmoud +2
Modern optical mouse sensors, with their advanced precision and high responsiveness, possess an often overlooked vulnerability: they can be exploited for side-channel attacks. This…
LLM4CVE: Enabling Iterative Automated Vulnerability Repair with Large Language Models
Mohamad Fakih, Rahul Dharmaji, Halima Bouzidi +3
Software vulnerabilities continue to be ubiquitous, even in the era of AI-powered code assistants, advanced static analysis tools, and the adoption of extensive testing frameworks.…
A Fly on the Wall -- Exploiting Acoustic Side-Channels in Differential Pressure Sensors
Yonatan Gizachew Achamyeleh, Mohamad Habib Fakih, Gabriel Garcia +2
Differential Pressure Sensors are widely deployed to monitor critical environments. However, our research unveils a previously overlooked vulnerability: their high sensitivity to p…
RPNR: Robust-Perception Neural Reshading
Fouad Afiouni, Mohamad Fakih, Joey Sleiman
Augmented Reality (AR) applications necessitates methods of inserting needed objects into scenes captured by cameras in a way that is coherent with the surroundings. Common AR appl…
LLM4PLC: Harnessing Large Language Models for Verifiable Programming of PLCs in Industrial Control Systems
Mohamad Fakih, Rahul Dharmaji, Yasamin Moghaddas +3
Although Large Language Models (LLMs) have established pre-dominance in automated code generation, they are not devoid of shortcomings. The pertinent issues primarily relate to the…
AudioFool: Fast, Universal and synchronization-free Cross-Domain Attack on Speech Recognition
Mohamad Fakih, Rouwaida Kanj, Fadi Kurdahi +1
Automatic Speech Recognition systems have been shown to be vulnerable to adversarial attacks that manipulate the command executed on the device. Recent research has focused on expl…