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O. Ojerinde

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#federated learning Open access Oct 2026

Blockchain-Enabled Federated Learning for Healthcare: An Empirical Evaluation of the Integrity Boundary, Byzantine Robustness, and Ledger Overhead

Federated learning enables healthcare institutions to train shared models without pooling patient records, but it does not by itself authenticate participants, verify that model updates arrive unaltered, or provide an auditable record of contributions. Permissioned blockchains are often proposed to address these gaps,...

O. Ojerinde, Jimoh Yusuf, D. Saba et al. · 1 citation
Open access Sep 2026

A Hybrid Consensus-Based Feature Selection Framework for Robust Housing Price Prediction

Accurate predictions are essential for investment planning and risk assessment in real estate markets. Machine learning techniques have increasingly been adopted to improve the accuracy of housing price prediction. However, numerous studies have reported the absence of comprehensive predictor sets, ineffective feature...

Josiah Afang Kalat, J. Alhassan, O. Ojerinde · 0 citations
Review Open access Sep 2026

Adversarially Robust and Explainable Graph Neural Networks for Fraud Detection in Dynamic Blockchain Networks: A Problem-Based Systematic Literature Review

Graph Neural Networks (GNNs) have emerged as an effective approach for blockchain fraud detection because they can model complex relationships among transactions and participating entities. However, existing GNN-based approaches remain limited by vulnerability to adversarial manipulation, limited explainability, contin...

O. Ojerinde, Ramatu Abubakar, Ajagun Abimbola Susan et al. · 0 citations
Review Open access Sep 2026

A Systematic Literature Review of Blockchain-Based Community Intelligence for Countering Criminal Logistics

The increasing prevalence of kidnappings and armed banditry has intensified the need to disrupt the logistical networks that sustain criminal operations. These criminal networks pose significant threats to national security, socio-economic stability, and public safety. Blockchain technology and decentralised threat int...

O. Ojerinde, J. Ojeniyi, A. Uduimoh et al. · 0 citations
Open access Aug 2026

Deep learning-based multi-speaker separation and speech enhancement for forensic audio analysis

A hybrid deep learning framework for multi-speaker separation and speech enhancement by integrating Gated Convolutional Neural Networks (GCNNs) for speech source separation with Long Short-Term Memory (LSTM) networks for temporal speech enhancement is proposed.

O. Ojerinde, R. Mudasiru, Ramatu Abubakar et al. · 0 citations
#graph neural networks Review Open access Sep 2026

Adversarially Robust and Explainable Graph Neural Networks for Fraud Detection in Dynamic Blockchain Networks: A Systematic Solution-Based Literature Review

Blockchain technology has revolutionized digital financial systems through decentralized, transparent, and secure transactions. However, the increasing sophistication of blockchain systems has coincided with the emergence of complex illicit activities, including ransomware transactions, Ponzi schemes, phishing, and mon...

O. Ojerinde, Ramatu Abubakar, B. Alenoghena et al. · 0 citations
Aug 2026

Blockchain Adoption and Governance Reform in Nigeria’s Petroleum Sector: Opportunities, Constraints, and Policy Pathways

In Nigeria's oil and gas industry, the problems of inconsistent reporting, lack of inter-agency collaboration, and untrustworthy state institutions continue to persist. This paper analyses the effects of blockchain technology on strengthening the processes of reporting and auditing petroleum production, given the curre...

O. Ojerinde, J. Mamman · 0 citations

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