Developing Multi-Factor Authentication and Biometric Verification Protocols for Enhancing Data Security in IoT Healthcare Devices

This paper introduces a Multi-Factor Authentication System for enhancing data security in IoT healthcare devices. The system comprises the Multi-Factor Authentication Algorithm (MFAA), Biometric Template Protection Algorithm (BTPA), Dynamic Risk-Based Authentication Algorithm (DRBAA), Adaptive Biometric Fusion Algorithm (ABFA), and Context-Aware Access Control Algorithm (CAACA). Through a comparative analysis, the proposed system consistently outperforms existing methods, demonstrating its potential for robust, context-aware, and adaptive user authentication. The ablation study delves into the individual contributions of each algorithm, emphasizing their collective strength in creating a secure and versatile authentication framework. The proposed system stands as a promising solution for addressing the evolving challenges of data security in the dynamic landscape of IoT healthcare.

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Publication Details

Published
2025-03-20
DOI
https://doi.org/10.1109/iccae64891.2025.10980555
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
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article

Developing Multi-Factor Authentication and Biometric Verification Protocols for Enhancing Data Security in IoT Healthcare Devices

Hamdan Alshehri
IoT and Edge/Fog Computing
article

Developing Multi-Factor Authentication and Biometric Verification Protocols for Enhancing Data Security in IoT Healthcare Devices

Hamdan Alshehri
article en

Abstract

This paper introduces a Multi-Factor Authentication System for enhancing data security in IoT healthcare devices. The system comprises the Multi-Factor Authentication Algorithm (MFAA), Biometric Template Protection Algorithm (BTPA), Dynamic Risk-Based Authentication Algorithm (DRBAA), Adaptive Biometric Fusion Algorithm (ABFA), and Context-Aware Access Control Algorithm (CAACA). Through a comparative analysis, the proposed system consistently outperforms existing methods, demonstrating its potential for robust, context-aware, and adaptive user authentication. The ablation study delves into the individual contributions of each algorithm, emphasizing their collective strength in creating a secure and versatile authentication framework. The proposed system stands as a promising solution for addressing the evolving challenges of data security in the dynamic landscape of IoT healthcare.

Jazan University (SA)
Industry, innovation and infrastructure
Openalex Percentile: Top 90%
IoT and Edge/Fog Computing
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