Features of Lightweight Proof of Stake Models for Enhancing Data Privacy in Telemedicine Systems: A Systematic Literature Review

Authors

  • Denis Wapukha Walumbe Department of Information Technology, Murang’a University of Technology, Murang’a, Kenya
  • Gabriel Ndugu Kamau Department of Information Technology, Murang’a University of Technology, Murang’a, Kenya
  • Jane Wanjiru Njuki Department of Information Technology, Murang’a University of Technology, Murang’a, Kenya

DOI:

https://doi.org/10.24203/d4dj5c90

Keywords:

Proof of Stake (PoS) , , Telemedicine Systems, Lightweight Models

Abstract

Proof of Stake (PoS) models are energy-efficient and require limited computational power. These features are critical in telemedicine environments, where resource-constrained devices must handle sensitive data securely. The growing need for auditable and privacy-preserving data storage in telemedicine underscores the importance of PoS models optimized for lightweight devices while complying with strict regulatory requirements, such as the Health Insurance Portability and Accountability Act (HIPAA).This study was guided by two research questions: (i) Which PoS models are lightweight and suitable for telemedicine? and (ii) What features make lightweight PoS models effective for privacy and efficiency in telemedicine? To address these questions, a systematic literature review (SLR) guided by the PICOC framework was conducted to investigate lightweight PoS models that can enhance privacy in telemedicine systems. Out of 2,394 papers studies screened, 55 were included in the analysis. The findings identified Algorand, Ouroboros Praos, Tendermint, Nxt, and Casper CBC as promising candidates. Key enabling features included lightweight voting mechanisms, such as Byzantine Agreement protocols and Verifiable Random Functions, as well as cryptographic techniques like symmetric encryption and multiparty computation. Performance metrics evaluated included latency, throughput, energy efficiency, and battery consumption, with Grey Relational Analysis ranking Algorand highest due to its low latency, high throughput, and minimal energy consumption.

Author Biographies

  • Gabriel Ndugu Kamau, Department of Information Technology, Murang’a University of Technology, Murang’a, Kenya

    A Senior Lecturer at Murang’a University of Technology in Nairobi, Kenya. His research primarily focuses on Information and Communication Technology for Development (ICT4D), Information Systems Philosophy, Computer Security, and Disruptive Technologies. Dr. Kamau has contributed significantly to the field, particularly through his work on cybersecurity, blockchain technology, and network security in developing countries. He has also published extensively on subjects such as e-government, mobile application security, and health information systems, with a strong emphasis on privacy-preserving models and practical solutions for data security in healthcare and public sectors.

  • Jane Wanjiru Njuki, Department of Information Technology, Murang’a University of Technology, Murang’a, Kenya

    a lecturer at Murang’a University of Technology, specializing in Information Technology, with a rich background in Information Systems and Educational Technology. Her research within the TVET (Technical and Vocational Education and Training) sector in Kenya focuses on digital transformation in education, including the adoption of digital libraries and ICT infrastructure in educational institutions. Dr. Njuki work addressed Information Security Metrics, developing a framework for ERP software. Her work also addresses e-learning, digital literacy, and improving security in enterprise systems.


                                

     

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Published

2025-10-28

How to Cite

Features of Lightweight Proof of Stake Models for Enhancing Data Privacy in Telemedicine Systems: A Systematic Literature Review. (2025). International Journal of Computer and Information Technology(2279-0764), 14(3). https://doi.org/10.24203/d4dj5c90

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