31 citations · 84 across the 11 of their papers we have counts for
12 papers
Multi-Class, Multi-Tier Network Intrusion Detection: A Comprehensive and Reproducible Benchmark
Yufeng Xin, Bryant Goseland, Mohamed Rahouti
Machine learning (ML) and deep learning (DL) have dominated Intrusion Detection System (IDS) research in recent years. Unfortunately, many existing studies have produced inflated r…
Joint UAV Activation and Placement for Post-Disaster Wireless Restoration via a Hybrid Quantum-Inspired Evolutionary Framework
Fatima Azzahraa Amarcha, Lahcen Hassine, Rachid Saadane +4
In post-disaster environments, the failure of terrestrial communication infrastructure necessitates the rapid deployment of unmanned aerial vehicles (UAVs) as aerial base stations…
Exploring Feature Importance and Explainability Towards Enhanced ML-Based DoS Detection in AI Systems
Paul Badu Yakubu, Evans Owusu, Lesther Santana +3
Denial of Service (DoS) attacks pose a significant threat in the realm of AI systems security, causing substantial financial losses and downtime. However, AI systems' high computat…
Enabling Trustworthy Federated Learning in Industrial IoT: Bridging the Gap Between Interpretability and Robustness
Senthil Kumar Jagatheesaperumal, Mohamed Rahouti, Ali Alfatemi +3
Federated Learning (FL) represents a paradigm shift in machine learning, allowing collaborative model training while keeping data localized. This approach is particularly pertinent…
Redefining DDoS Attack Detection Using A Dual-Space Prototypical Network-Based Approach
Fernando Martinez, Mariyam Mapkar, Ali Alfatemi +4
Distributed Denial of Service (DDoS) attacks pose an increasingly substantial cybersecurity threat to organizations across the globe. In this paper, we introduce a new deep learnin…
Nonlinear Transformations Against Unlearnable Datasets
Thushari Hapuarachchi, Jing Lin, Kaiqi Xiong +2
Automated scraping stands out as a common method for collecting data in deep learning models without the authorization of data owners. Recent studies have begun to tackle the priva…
Advancing DDoS Attack Detection: A Synergistic Approach Using Deep Residual Neural Networks and Synthetic Oversampling
Ali Alfatemi, Mohamed Rahouti, Ruhul Amin +3
Distributed Denial of Service (DDoS) attacks pose a significant threat to the stability and reliability of online systems. Effective and early detection of such attacks is pivotal…
Blockchain-Based Security Architecture for Unmanned Aerial Vehicles in B5G/6G Services and Beyond: A Comprehensive Approach
Senthil Kumar Jagatheesaperumal, Mohamed Rahouti, Kaiqi Xiong +3
Unmanned Aerial Vehicles (UAVs), previously favored by enthusiasts, have evolved into indispensable tools for effectively managing disasters and responding to emergencies. For exam…
Enhancing ML-Based DoS Attack Detection Through Combinatorial Fusion Analysis
Evans Owusu, Mohamed Rahouti, D. Frank Hsu +2
Mitigating Denial-of-Service (DoS) attacks is vital for online service security and availability. While machine learning (ML) models are used for DoS attack detection, new strategi…
Explainable Artificial Intelligence for Drug Discovery and Development -- A Comprehensive Survey
Roohallah Alizadehsani, Solomon Sunday Oyelere, Sadiq Hussain +5
The field of drug discovery has experienced a remarkable transformation with the advent of artificial intelligence (AI) and machine learning (ML) technologies. However, as these AI…
A Decentralized Cooperative Navigation Approach for Visual Homing Networks
Mohamed Rahouti, Damian Lyons, Senthil Kumar Jagatheesaperumal +1
Visual homing is a lightweight approach to visual navigation. Given the stored information of an initial 'home' location, the navigation task back to this location is achieved from…
ML Attack Models: Adversarial Attacks and Data Poisoning Attacks
Jing Lin, Long Dang, Mohamed Rahouti +1
Many state-of-the-art ML models have outperformed humans in various tasks such as image classification. With such outstanding performance, ML models are widely used today. However,…