Towards a robust data privacy framework for IoT based health monitoring system

Nowadays, the need for a robust data privacy framework in health monitoring system is driven because the health sector is a prime target for cyber-attacks due to the high value of sensitive data on the cloud server storage. This paper presents a robust data privacy framework designed for health monitoring systems, addressing the critical need for secure handling of sensitive patient information. The proposed framework integrates hybrid consensus mechanism, ring signature mechanism, and data authentication mechanism to ensure sustainable and secure blockchain infrastructure, robust framework, and accuracy and consistency of data. Moreover, Security-Performance Efficiency Metric show that the proposed robust data privacy framework is effective and efficient in compare to existing framework for improving transaction processing and blockchain administration. • Comprehensive Privacy Architecture: A robust health monitoring system data privacy architecture designed to protect sensitive patient data. • Key Technologies: Utilizes blockchain for Hybrid Consensus Mechanism (HCM), ring signatures, and data exchange. • Performance Improvements: (i) Transaction Volume: 33% increase; (ii) Validator Demand: 19% reduction; (iii) Block Sizes: 23% decrease; (iv) Validation Time: 12.4% reduction per validator. • Efficiency and Effectiveness: Demonstrated superiority over existing methods in terms of transaction processing and blockchain management. • Sustainable and Secure Infrastructure: Provides a robust framework for accurate and consistent data, enhancing vulnerability detection and mitigation.

Authors

Institutions

Publication Details

Journal
e-Prime - Advances in Electrical Engineering Electronics and Energy
Published
2025-03-23
DOI
https://doi.org/10.1016/j.prime.2025.100961
Citations
2
Primary Topic
User Authentication and Security Systems
Type
article
Field-Weighted Citation Impact
6.49
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Towards a robust data privacy framework for IoT based health monitoring system

Punam Prabha, Kakali Chatterjee
2 citations
e-Prime - Advances in Electrical Engineering Electronics and Energy
User Authentication and Security Systems
6.49
article

Towards a robust data privacy framework for IoT based health monitoring system

Punam Prabha, Kakali Chatterjee
article en
2 citations

Abstract

Nowadays, the need for a robust data privacy framework in health monitoring system is driven because the health sector is a prime target for cyber-attacks due to the high value of sensitive data on the cloud server storage. This paper presents a robust data privacy framework designed for health monitoring systems, addressing the critical need for secure handling of sensitive patient information. The proposed framework integrates hybrid consensus mechanism, ring signature mechanism, and data authentication mechanism to ensure sustainable and secure blockchain infrastructure, robust framework, and accuracy and consistency of data. Moreover, Security-Performance Efficiency Metric show that the proposed robust data privacy framework is effective and efficient in compare to existing framework for improving transaction processing and blockchain administration. • Comprehensive Privacy Architecture: A robust health monitoring system data privacy architecture designed to protect sensitive patient data. • Key Technologies: Utilizes blockchain for Hybrid Consensus Mechanism (HCM), ring signatures, and data exchange. • Performance Improvements: (i) Transaction Volume: 33% increase; (ii) Validator Demand: 19% reduction; (iii) Block Sizes: 23% decrease; (iv) Validation Time: 12.4% reduction per validator. • Efficiency and Effectiveness: Demonstrated superiority over existing methods in terms of transaction processing and blockchain management. • Sustainable and Secure Infrastructure: Provides a robust framework for accurate and consistent data, enhancing vulnerability detection and mitigation.

e-Prime - Advances in Electrical Engineering Electronics and EnergyVol. 12
National Institute of Technology Patna (IN)
Openalex Percentile: Top 5%
User Authentication and Security Systems
6.49
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.