13 citations · 24 across the 4 of their papers we have counts for
4 papers
Interpretable Ransomware Detection Using Hybrid Large Language Models: A Comparative Analysis of BERT, RoBERTa, and DeBERTa Through LIME and SHAP
Elodie Mutombo Ngoie, Mike Nkongolo Wa Nkongolo, Peace Azugo +1
Ransomware continues to evolve in complexity, making early and explainable detection a critical requirement for modern cybersecurity systems. This study presents a comparative anal…
Ransomware detection using stacked autoencoder for feature selection
Mike Nkongolo, Mahmut Tokmak
The aim of this study is to propose and evaluate an advanced ransomware detection and classification method that combines a Stacked Autoencoder (SAE) for precise feature selection…
Stacking an autoencoder for feature selection of zero-day threats
Mahmut Tokmak, Mike Nkongolo
Zero-day attack detection plays a critical role in mitigating risks, protecting assets, and staying ahead in the evolving threat landscape. This study explores the application of s…
Zero-Day Threats Detection for Critical Infrastructures
Mike Nkongolo, Mahmut Tokmak
Technological advancements in various industries, such as network intelligence, vehicle networks, e-commerce, the Internet of Things (IoT), ubiquitous computing, and cloud-based ap…