46 citations · 149 across the 12 of their papers we have counts for
12 papers
Hybrid ResNet-1D-BiGRU with Multi-Head Attention for Cyberattack Detection in Industrial IoT Environments
Afrah Gueriani, Hamza Kheddar, Ahmed Cherif Mazari
This study introduces a hybrid deep learning model for intrusion detection in Industrial IoT (IIoT) systems, combining ResNet-1D, BiGRU, and Multi-Head Attention (MHA) for effectiv…
SE-Enhanced ViT and BiLSTM-Based Intrusion Detection for Secure IIoT and IoMT Environments
Afrah Gueriani, Hamza Kheddar, Ahmed Cherif Mazari +2
With the rapid growth of interconnected devices in Industrial and Medical Internet of Things (IIoT and MIoT) ecosystems, ensuring timely and accurate detection of cyber threats has…
A Robust Cross-Domain IDS using BiGRU-LSTM-Attention for Medical and Industrial IoT Security
Afrah Gueriani, Hamza Kheddar, Ahmed Cherif Mazari +1
The increased Internet of Medical Things IoMT and the Industrial Internet of Things IIoT interconnectivity has introduced complex cybersecurity challenges, exposing sensitive data,…
NeurIPS 2024 ML4CFD Competition: Results and Retrospective Analysis
Mouadh Yagoubi, David Danan, Milad Leyli-Abadi +15
The integration of machine learning (ML) into the physical sciences is reshaping computational paradigms, offering the potential to accelerate demanding simulations such as computa…
Adaptive Cyber-Attack Detection in IIoT Using Attention-Based LSTM-CNN Models
Afrah Gueriani, Hamza Kheddar, Ahmed Cherif Mazari
The rapid expansion of the industrial Internet of things (IIoT) has introduced new challenges in securing critical infrastructures against sophisticated cyberthreats. This study pr…
Automatic Speech Recognition with BERT and CTC Transformers: A Review
Noussaiba Djeffal, Hamza Kheddar, Djamel Addou +2
This review paper provides a comprehensive analysis of recent advances in automatic speech recognition (ASR) with bidirectional encoder representations from transformers BERT and c…
Deep Reinforcement Learning for Intrusion Detection in IoT: A Survey
Afrah Gueriani, Hamza Kheddar, Ahmed Cherif Mazari
The rise of new complex attacks scenarios in Internet of things (IoT) environments necessitate more advanced and intelligent cyber defense techniques such as various Intrusion Dete…
Enhancing IoT Security with CNN and LSTM-Based Intrusion Detection Systems
Afrah Gueriani, Hamza Kheddar, Ahmed Cherif Mazari
Protecting Internet of things (IoT) devices against cyber attacks is imperative owing to inherent security vulnerabilities. These vulnerabilities can include a spectrum of sophisti…
Action Recognition with Deep Multiple Aggregation Networks
Ahmed Mazari, Hichem Sahbi
Most of the current action recognition algorithms are based on deep networks which stack multiple convolutional, pooling and fully connected layers. While convolutional and fully c…
Deep hierarchical pooling design for cross-granularity action recognition
Ahmed Mazari, Hichem Sahbi
In this paper, we introduce a novel hierarchical aggregation design that captures different levels of temporal granularity in action recognition. Our design principle is coarse-to-…
Human Action Recognition with Multi-Laplacian Graph Convolutional Networks
Ahmed Mazari, Hichem Sahbi
Convolutional neural networks are nowadays witnessing a major success in different pattern recognition problems. These learning models were basically designed to handle vectorial d…
Human Action Recognition with Deep Temporal Pyramids
Ahmed Mazari, Hichem Sahbi
Deep convolutional neural networks (CNNs) are nowadays achieving significant leaps in different pattern recognition tasks including action recognition. Current CNNs are increasingl…