The increased sophistication of fraudulent schemes and money laundering techniques is placing significant pressure on conventional fraud detection systems and models. This study presents a hybrid framework that integrates Graph Neural Networks, Federated Learning and Explainable Artificial Intelligence for real-time fr...
Omorogie Michael, O. M. Nwakeze, Agubosim Chuka Charles et al.· International journal of re...· 0 citations
This study designs and develops an Explainable Artificial Intelligence framework for real-time cyber-threat detection and response in enterprise information systems. CICIDS2017 cyber-threat dataset was used to develop and evaluate the framework. Duplicate records, missing data values, identifiers, and variables with ze...
Omorogie Michael, O. M. Nwakeze, Chekwube Georgina Nwankwo et al.· Current Journal of Engineeri...· 0 citations
The design and simulation-based implementation of a context-aware intelligent surveillance system that fuses CCTV video streams with Internet of Things sensor data to enhance detection accuracy and system responsiveness, specifically for indoor fire detection is presented.
O. M. Nwakeze, Ugoji Frank Godric Chidubem, Nwafor Anthony Chigozie et al.· Journal of Engineering Resea...· 0 citations
Nigeria faces challenges in the accurate diagnosis of respiratory diseases such as tuberculosis (TB), pneumonia, and COVID-19 because of limited radiology resources and stringent patient-privacy requirements. Deep learning models can provide strong diagnostic performance but often rely on centralised data, raising ethi...
Oboti Nwamaka Peace, O. M. Nwakeze, Sunday Stephen Okika et al.· Journal of the Nigerian Soci...· 0 citations
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