Blockchain-Enabled Secure Data Sharing Framework for Healthcare IoT Devices
Abstract
Medical data security challenges have increased dramatically because healthcare institutions continue to integrate more Internet of Things devices to deliver data-driven clinical services. Access control systems based on RBAC, ABAC and MAC do not meet the requirements of flexible protection and scalable and context-aware security which are needed for dynamic healthcare environments. The research objective focuses on creating a resilient decentralized access control solution which delivers secure time-sensitive access permissions in healthcare IoT systems. A blockchain-based hybrid access control framework with RBAC and ABAC provides the solution to meet this requirement. A dual mechanism of smart contracts and IPFS storage runs the model while variables and user-facing elements shift based on environmental characteristics and individual circumstances. Results from experimental evaluation show that this proposed framework delivers 96.5% access precision together with policy evaluation times below 3.2 ms and 120 ms response times while handling 74 transactions per second while remaining affordable at $2.1 and demanding 45 to 52 MB from critical system memory. The obtained results demonstrate better scalability together with enhanced performance and adaptability when compared to using ABAC, RBAC and MAC singularly. Healthcare IoT systems should implement a blockchain-based hybrid access control system as an optimal method to secure data sharing in real-time resource-constrained scenarios.
Keywords
References
J. P. Abasaheb and S. V. Mallapur, “Blockchain-integrated secure healthcare information sharing via advanced Blowfish encryption standard with optimal key generation,” Trans. Emerg. Telecommun. Technol., vol. 36, no. 3, e70077, 2025.
A. A. Abdellatif, K. Shaban, and A. Massoud, “Blockchain-enabled distributed learning for enhanced smart grid security and efficiency,” Comput. Electr. Eng., vol. 123, p. 110012, 2025.
M. T. Ahad, M. M. Morshed, A. S. Atkins, and H. Yu, “An IoT-enabled blockchain system to secure medical data,” in Digital Twin, Blockchain, and Sensor Networks in the Healthy and Mobile City. Amsterdam, The Netherlands: Elsevier, 2025, pp. 121–146.
M. Mejail, B. K. Nestares, and L. Gravano, “The evolution of telecommunications: Analog to digital,” Prog. Electron. Commun. Eng., vol. 2, no. 1, pp. 16–26, 2024, doi: 10.31838/PECE/02.01.02.
I. Ahmed, M. A. Syed, M. Maaruf, and M. Khalid, “Distributed computing in multi-agent systems: A survey of decentralized machine learning approaches,” Computing, vol. 107, no. 1, p. 2, 2025.
P. Bagchi, A. Bisht, A. K. Das, N. Saxena, and M. S. Hossain, “Designing quantum-safe lattice-based multi-authority CP-ABE scheme for blockchain-enabled IoT-based consumer healthcare electronics,” IEEE Trans. Consum. Electron., early access, 2025.
O. Cheikhrouhou, K. Mershad, F. Jamil, R. Mahmud, A. Koubaa, and S. R. Moosavi, “A lightweight blockchain and fog-enabled secure remote patient monitoring system,” Internet Things, vol. 22, p. 100691, 2023.
S. B. Erukala et al., “A secure end-to-end communication framework for cooperative IoT networks using hybrid blockchain system,” Sci. Rep., vol. 15, no. 1, p. 11077, 2025.
M. Harish et al., “An IoT-based blockchain-enabled secure storage for healthcare systems,” in Explainable IoT Applications: A Demystification. Cham, Switzerland: Springer Nature, 2025, pp. 99–113.
K. Choset and J. Bindal, “Using FPGA-based embedded systems for accelerated data processing analysis,” SCCTS J. Embedded Syst. Des. Appl., vol. 2, no. 1, pp. 79–85, 2025.
S. Kabra, S. Sharma, and M. Sachdeva, “Blockchain: A new frontier in secure patient data management,” in Blockchain-Enabled Solutions for the Pharmaceutical Industry, 2025, pp. 319–334.
A. A. Khan et al., “BDLT-IoMT—a novel architecture: SVM machine learning for robust and secure data processing in Internet of Medical Things with blockchain cybersecurity,” J. Supercomput., vol. 81, no. 1, pp. 1–22, 2025.
S. Khan et al., “A blockchain-enabled AI-driven secure searchable encryption framework for medical IoT systems,” IEEE J. Biomed. Health Inform., early access, 2025.
A. James, W. Thomas, and B. Samuel, “IoT-enabled smart healthcare systems: Improvements to remote patient monitoring and diagnostics,” J. Wireless Sensor Netw. IoT, vol. 2, no. 2, pp. 11–19, 2025.
D. Y. R. Kulkarni, D. S. Sugave, D. B. Jagdale, and V. Gutte, “Spinal PMDMNN: A new blockchain-based IoT network for healthcare classification,” Aust. J. Electr. Electron. Eng., pp. 1–15, 2025.
S. M. Lakshmi, M. Malathi, and K. Mythili, “Blockchain-enabled security for smart medicine vending machines handling expired medications,” in Blockchain-Enabled Solutions for the Pharmaceutical Industry, 2025, pp. 189–206.
M. Li et al., “Blockchain-based medical data asset sharing framework for healthcare 4.0,” IEEE Trans. Ind. Informat., early access, 2025.
T. Mazhar et al., “Generative AI, IoT, and blockchain in healthcare: Application, issues, and solutions,” Discover Internet Things, vol. 5, no. 1, p. 5, 2025.
A. Mazid, S. Kirmani, M. Abid, and V. Pawar, “A secure and efficient framework for Internet of Medical Things through blockchain-driven customized federated learning,” Cluster Comput., vol. 28, no. 4, p. 225, 2025.
K. P. Uvarajan, “Advances in quantum computing: Implications for engineering and science,” Innov. Rev. Eng. Sci., vol. 1, no. 1, pp. 21–24, 2024, doi: 10.31838/INES/01.01.05.
R. Mehla, R. Garg, and M. A. Khan, “Privacy-preserving solution for data sharing in IoT-based smart consumer electronic devices for healthcare,” IEEE Trans. Consum. Electron., early access, 2025.
S. Meisami, S. Meisami, M. Yousefi, and M. R. Aref, “Combining blockchain and IoT for decentralized healthcare data management,” arXiv:2304.00127, 2023.
D. P. Mishra, B. Rajeev, S. R. Mallick, R. K. Lenka, and S. R. Salkuti, “Efficient blockchain-based solution for secure medical record management,” Int. J. Inf. Commun. Technol., vol. 14, no. 1, pp. 59–67, 2025.
B. K. Mohanta, A. I. Awad, M. K. Dehury, H. Mohapatra, and M. K. Khan, “Protecting IoT-enabled healthcare data at the edge: Integrating blockchain, AES, and off-chain decentralized storage,” IEEE Internet Things J., early access, 2025.
V. K. Nassa et al., “Blockchain-enabled secure data sharing and communication in IoT networks,” in Interdisciplinary Approaches to AI, Internet of Everything, and Machine Learning. Hershey, PA, USA: IGI Global Scientific Publishing, 2025, pp. 131–142.
S. Prajapat, P. Kumar, A. K. Das, and G. Muhammad, “Generative AI-enabled quantum encryption algorithm for securing IoT-based healthcare application using blockchain,” IEEE Internet Things J., early access, 2025.
G. G. Bianchi and F. M. Rossi, “Reconfigurable computing platforms for bioinformatics applications,” SCCTS Trans. Reconfigurable Comput., vol. 2, no. 1, pp. 16–23, 2025.
H. Rastogi, A. N. Tripathi, and B. Sharma, “Blockchain technology for securing healthcare data in cyber-physical systems,” in Artificial Intelligence and Cybersecurity in Healthcare, 2025, pp. 85–112.
A. Rizzardi, S. Sicari, and A. Coen-Porisini, “IoT-driven blockchain to manage the healthcare supply chain and protect medical records,” Future Gener. Comput. Syst., vol. 161, pp. 415–431, 2024.
P. Roy, S. H. T. Sherazi, M. J. M. Delda, M. Maqsood, and M. Ahmad, “Secure data sharing in healthcare: A blockchain and digital twins approach,” in Digital Twins for Sustainable Healthcare in the Metaverse. Hershey, PA, USA: IGI Global Scientific Publishing, 2025, pp. 255–286.
N. Sahu and I. Karthikeyan, “Secure privacy-preserving resolution adaptive data sharing in hybrid blockchain-controlled medical IoT environment,” Int. J. Intell. Eng. Syst., vol. 18, no. 1, 2024.
G. SarojiniKaruppusamy and S. M. Kumar, “TwoFish-integrated blockchain for secure and optimized healthcare data processing in IoT-edge-cloud system,” Trans. Emerg. Telecommun. Technol., vol. 36, no. 3, e70076, 2025.
Y. Tang, K. Wang, D. Niyato, J. Li, O. A. Dobre, and T. Q. Duong, “Secure data sharing and prediction with digital twin and blockchain in healthcare,” IEEE Commun. Mag., early access, 2025.
K. Tlemçani et al., “Empowering diabetes management through blockchain and edge computing: A systematic review of healthcare innovations and challenges,” IEEE Access, early access, 2025.
J. A. Venice, R. Vettriselvan, D. Rajesh, P. Xavier, and H. J. Shanthi, “Optimizing performance metrics in blockchain-enabled AI/ML data analytics: Assessing cognitive IoT,” in Enhancing Automated Decision-Making Through AI. Hershey, PA, USA: IGI Global Scientific Publishing, 2025, pp. 97–122.
G. Verma and S. Yadav, “Blockchain for management of healthcare data,” in Blockchain and Digital Twin for Smart Healthcare. Amsterdam, The Netherlands: Elsevier, 2025, pp. 419–437.
P. Vinayasree and A. M. Reddy, “A reliable and secure permissioned blockchain-assisted data transfer mechanism in healthcare-based cyber-physical systems,” Concurrency Comput.: Pract. Exp., vol. 37, no. 3, e8378, 2025.
A. P. Vinnarasi and R. Dayana, “OSL-ABE: An optimal secure and lightweight attribute-based encryption method for blockchain-enabled IoT-based healthcare systems,” Neural Comput. Appl., vol. 37, no. 1, pp. 123–148, 2025.
R. Thompson and L. Sonntag, “How medical cyber-physical systems are making smart hospitals a reality,” J. Integr. VLSI, Embedded Comput. Technol., vol. 2, no. 1, pp. 20–29, 2025, doi: 10.31838/JIVCT/02.01.03.
P. Whig, R. Sharma, N. Yathiraju, A. Jain, and S. Sharma, “Blockchain-enabled secure federated learning systems for advancing privacy and trust in decentralized AI,” in Model Optimization Methods for Efficient and Edge AI: Federated Learning Architectures, Frameworks and Applications, 2024, pp. 321–340.
DOI: https://doi.org/10.52088/ijesty.v5i2.1520
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