Privacy-Preserving Machine Learning Technique Using One-Way Hashing for Enhancing Data Security in the Nigerian Healthcare Ecosystem

Authors: Damang, F.S., and Gilbert I.O. Aimufua

Affiliation: Department of Computer Science, Faculty of Natural and Applied Sciences, Nasarawa State University, Keffi, Nigeria

Corresponding Author: [email protected]

February 15, 2026

SIAR-Global Journal of Computer, Information & Library Science

DOI: 10.5281/zenodo.18643524

Privacy-Preserving Machine Learning Technique Using One-Way Hashing for Enhancing Data Security in the Nigerian Healthcare Ecosystem

Research Article Multidisciplinary

Abstract

Safeguarding healthcare data in Nigeria remains a pressing challenge, complicated by fragmented infrastructure, limited resources, and evolving regulatory frameworks. This paper presents a conceptual analysis of one-way hashing as a lightweight cryptographic technique for pseudonymizing patient identifiers within federated learning pipelines. By situating hashing in contrast to heavier cryptographic methods such as homomorphic encryption and secure multiparty computation, the study highlights its relative efficiency, scalability, and compliance with the Nigeria Data Protection Regulation (NDPR, 2019) and the Nigeria Data Protection Act (NDPA, 2023). Through analytical benchmarking and illustrative scenarios, hashing is shown to offer a pragmatic balance between privacy preservation and operational feasibility in resource-constrained healthcare environments. The paper concludes that one-way hashing provides a viable conceptual pathway for operationalizing privacy-preserving machine learning in Nigerian healthcare systems, while laying the foundation for future empirical validation.

Keywords

Healthcare data protection; Federated learning; One-way hashing; Pseudonymizations; Privacy-preserving machine learning; Conceptual analysis; Nigeria Data Protection Regulation (NDPR); Nigeria Data Protection Act (NDPA); Cryptographic complexity; Resource-constrained environments

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Damang, F.S., and Gilbert I.O. Aimufua (2026). Privacy-Preserving Machine Learning Technique Using One-Way Hashing for Enhancing Data Security in the Nigerian Healthcare Ecosystem. SIAR-Global Journal of Computer, Information & Library Science, Vol. 2, No. 1. DOI: 10.5281/zenodo.18643524

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Privacy-Preserving Machine Learning Technique Using One-Way Hashing for Enhancing Data Security in the Nigerian Healthcare Ecosystem

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SIAR-Global Journal of Computer, Information & Library Science