4 citations · 4 across the 9 of their papers we have counts for
9 papers
How the Graph Construction Technique Shapes Performance in IoT Botnet Detection
Hassan Wasswa, Hussein Abbass, Timothy Lynar
The increasing incidence of IoT-based botnet attacks has driven interest in advanced learning models for detection. Recent efforts have focused on leveraging attention mechanisms t…
Toward Real-World IoT Security: Concept Drift-Resilient IoT Botnet Detection via Latent Space Representation Learning and Alignment
Hassan Wasswa, Timothy Lynar
Although AI-based models have achieved high accuracy in IoT threat detection, their deployment in enterprise environments is constrained by reliance on stationary datasets that fai…
A Quantized VAE-MLP Botnet Detection Model: A Systematic Evaluation of Quantization-Aware Training and Post-Training Quantization Strategies
Hassan Wasswa, Hussein Abbass, Timothy Lynar
In an effort to counter the increasing IoT botnet-based attacks, state-of-the-art deep learning methods have been proposed and have achieved impressive detection accuracy. However,…
Are GNNs Worth the Effort for IoT Botnet Detection? A Comparative Study of VAE-GNN vs. ViT-MLP and VAE-MLP Approaches
Hassan Wasswa, Hussein Abbass, Timothy Lynar
Due to the exponential rise in IoT-based botnet attacks, researchers have explored various advanced techniques for both dimensionality reduction and attack detection to enhance IoT…
Graph Attention Neural Network for Botnet Detection: Evaluating Autoencoder, VAE and PCA-Based Dimension Reduction
Hassan Wasswa, Hussein Abbass, Timothy Lynar
With the rise of IoT-based botnet attacks, researchers have explored various learning models for detection, including traditional machine learning, deep learning, and hybrid approa…
Preserving Seasonal and Trend Information: A Variational Autoencoder-Latent Space Arithmetic Based Approach for Non-stationary Learning
Hassan Wasswa, Aziida Nanyonga, Timothy Lynar
AI models have garnered significant research attention towards predictive task automation. However, a stationary training environment is an underlying assumption for most models an…
IoT Botnet Detection: Application of Vision Transformer to Classification of Network Flow Traffic
Hassan Wasswa, Timothy Lynar, Aziida Nanyonga +1
Despite the demonstrated effectiveness of transformer models in NLP, and image and video classification, the available tools for extracting features from captured IoT network flow…
Impact of Latent Space Dimension on IoT Botnet Detection Performance: VAE-Encoder Versus ViT-Encoder
Hassan Wasswa, Aziida Nanyonga, Timothy Lynar
The rapid evolution of Internet of Things (IoT) technology has led to a significant increase in the number of IoT devices, applications, and services. This surge in IoT devices, al…
Investigating two super-resolution methods for downscaling precipitation: ESRGAN and CAR
Campbell D. Watson, Chulin Wang, Timothy Lynar +1
In an effort to provide optimal inputs to downstream modeling systems (e.g., a hydrodynamics model that simulates the water circulation of a lake), we hereby strive to enhance reso…