Blockchain for Secure EHRs Sharing of Mobile Cloud Based E-Health Systems

By Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, Aruna Prasad Seneviratne. IEEE Access, 2019

398 citations recorded by the source corpus.

Recent years have witnessed a paradigm shift in the storage of Electronic Health Records (EHRs) on mobile cloud environments, where mobile devices are integrated with cloud computing to facilitate medical data exchanges among patients and healthcare providers. This advanced model enables healthcare services with low operational cost, high flexibility, and EHRs availability. However, this new paradigm also raises concerns about data privacy and network security for e-health systems. How to reliably share EHRs among mobile users while guaranteeing high-security levels in the mobile cloud is a challenging issue. In this paper, we propose a novel EHRs sharing framework that combines blockchain and the decentralized interplanetary file system (IPFS) on a mobile cloud platform. Particularly, we design a trustworthy access control mechanism using smart contracts to achieve secure EHRs sharing among different patients and medical providers. We present a prototype implementation using Ethereum blockchain in a real data sharing scenario on a mobile app with Amazon cloud computing. The empirical results show that our proposal provides an effective solution for reliable data exchanges on mobile clouds while preserving sensitive health information against potential threats. The system evaluation and security analysis also demonstrate the performance improvements in lightweight access control design, minimum network latency with high security and data privacy levels, compared to the existing data sharing models.

Subfields: Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/9035c4d55deebbc3b6222baca9882812d707ff4d

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Citations in the corpus

Federated Learning Meets Blockchain in Edge Computing: Opportunities and Challenges (2021, background): “In this context, differential privacy techniques can be employed so that model computation is considered to be differentially private if the output is independent to particular data points from input data.”
Federated Learning for Internet of Things: A Comprehensive Survey (2021, methodology): “Moreover, fine-grained data access policies on blockchain, such as smart contracts [71], can provide reliable authentication for federated health data processing.”
6G Internet of Things: A Comprehensive Survey (2021, methodology): “A synergetic optimization solution for UAV trajectory planning and subslot allocation is derived by portioning the downlink energy transfer subslot and uplink information transmission subslot.”
Blockchain Meets Cloud Computing: A Survey (2020, background): “Nugyen et al. [86] addressed the scenario of medical records sharing and examined the performance of BAC.”
Blockchain for 5G and Beyond Networks: A State of the Art Survey (2019, neutral): “systems [242], [243].”