8 citations · 15 across the 4 of their papers we have counts for
6 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…
Deep Learning Network-Temporal Models For Traffic Prediction
Yufeng Xin, Ethan Fan
Accurate prediction of multivariate time series is essential for emerging network intelligent control, observability, and management functions. Existing statistical-based and shall…
Automated and Explainable Denial of Service Analysis for AI-Driven Intrusion Detection Systems
Paul Badu Yakubu, Lesther Santana, Mohamed Rahouti +3
With the increasing frequency and sophistication of Distributed Denial of Service (DDoS) attacks, it has become critical to develop more efficient and interpretable detection metho…
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…
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…
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…