activity
20232026
most citedPhysical Adversarial Attacks For Camera-based Smart Systems: Current Trends, Categorization, Applications, Research Challenges, and Future Outlook

5 citations · 6 across the 8 of their papers we have counts for

collaborators
Showing cs.CRShow all

8 papers · 1 filter

cs.CR2026

VulnScout-C: A Lightweight Transformer for C Code Vulnerability Detection

Aymen Lassoued, Nacef Mbarek, Bechir Dardouri +3

Vulnerability detection in C programs is a critical challenge in software security. Although large language models (LLMs) achieve strong detection performance, their multi-billion-…

cs.CR2026

PatchBlock: A Lightweight Defense Against Adversarial Patches for Embedded EdgeAI Devices

Nandish Chattopadhyay, Abdul Basit, Amira Guesmi +3

Adversarial attacks pose a significant challenge to the reliable deployment of machine learning models in EdgeAI applications, such as autonomous driving and surveillance, which re…

cs.CR2025

Cybersecurity of High-Altitude Platform Stations: Threat Taxonomy, Attacks and Defenses with Standards Mapping - DDoS Attack Use Case

Chaouki Hjaiji, Bassem Ouni, Mohamed-Slim Alouini

High-Altitude Platform Stations (HAPS) are emerging stratospheric nodes within non-terrestrial networks. We provide a structured overview of HAPS subsystems and principal communica…

cs.CR2024

Exploring the Robustness and Transferability of Patch-Based Adversarial Attacks in Quantized Neural Networks

Amira Guesmi, Bassem Ouni, Muhammad Shafique

Quantized neural networks (QNNs) are increasingly used for efficient deployment of deep learning models on resource-constrained platforms, such as mobile devices and edge computing…

cs.CR2023

Enhancing IoT Security via Automatic Network Traffic Analysis: The Transition from Machine Learning to Deep Learning

Mounia Hamidouche, Eugeny Popko, Bassem Ouni

This work provides a comparative analysis illustrating how Deep Learning (DL) surpasses Machine Learning (ML) in addressing tasks within Internet of Things (IoT), such as attack cl…

cs.CR20231 cited

DefensiveDR: Defending against Adversarial Patches using Dimensionality Reduction

Nandish Chattopadhyay, Amira Guesmi, Muhammad Abdullah Hanif +2

Adversarial patch-based attacks have shown to be a major deterrent towards the reliable use of machine learning models. These attacks involve the strategic modification of localize…