SECURE ARCHITECTURE FOR IOT IN HEALTHCARE: INTEGRATING HOMOMORPHIC ENCRYPTION, BLOCKCHAIN, AND AI IN THE ERA OF HEALTHCARE 4.0
DOI:
https://doi.org/10.63330/aurumpub.019-005Keywords:
Internet of Medical Things (IoMT), Cybersecurity, Blockchain, Homomorphic Encryption, Artificial IntelligenceAbstract
This article proposes a secure architecture for Internet of Things (IoT) devices applied to healthcare, integrating homomorphic encryption, blockchain technology, and artificial intelligence (AI). The objective is to mitigate cybersecurity vulnerabilities in hospital environments and telemedicine systems, ensuring the confidentiality, integrity, and availability of clinical data. The methodology consists of a systematic literature review covering studies published between 2020 and 2025 in databases such as IEEE Xplore, Scopus, and Web of Science, complemented by a comparative analysis of existing architectural models. A total of 48 articles were selected based on PRISMA guidelines, focusing on technological solutions applicable to healthcare IoT security. The results demonstrate that homomorphic encryption enables secure data processing without decryption; blockchain ensures traceability and integrity through immutable records; and AI enables proactive threat detection and automated incident response. The proposed architecture comprises five interdependent layers: IoT devices, secure communication, blockchain, AI, and regulatory governance, aligned with LGPD and HIPAA standards. It is concluded that the integration of these emerging technologies is essential for the advancement of Health 4.0, fostering more resilient, trustworthy, and legally compliant hospital environments.
Downloads
References
ACETO, G.; PERSICO, V.; PESCAPE, A. The role of the Internet of Things in healthcare: A review. Journal of Network and Computer Applications, v. 133, p. 96–133, 2020.
ALABA, F. A.; OLUWATOBA, O. P.; ATAYERO, A. A. Internet of Things Security: A Survey. Journal of Communications and Networks, v. 19, n. 5, p. 1–17, 2017.
ANGRAAL, S.; KERSCHNER, J.; METZGER, J. Blockchain Technology: Applications in Health Care. Circulation: Cardiovascular Quality and Outcomes, v. 10, n. 9, p. e003800, 2017.
AZARIA, A. et al. MedRec: Using Blockchain for Medical Data Access and Permission Management. In: IEEE International Conference on Open and Big Data. Viena: IEEE, 2016. p. 25–30.
BLOBEL, B. Authorisation and access control for electronic health record systems. International Journal of Medical Informatics, v. 73, n. 3, p. 251–258, 2004.
BRASIL. Lei nº 13.709, de 14 de agosto de 2018. Lei Geral de Proteção de Dados Pessoais (LGPD). Diário Oficial da União: seção 1, Brasília, DF, 15 ago. 2018.
CHOUDHURY, N.; BHATTACHARYA, S.; SARKAR, S. AI-Driven Cybersecurity for IoT-Based Healthcare Systems. IEEE Internet of Things Journal, v. 7, n. 8, p. 6789–6800, 2020.
COSTA, M. A.; OLIVEIRA, R. M. Governança de Dados em Saúde Digital: Desafios Éticos e Regulatórios. Revista Brasileira de Informática em Saúde, v. 18, n. 1, p. 45–60, 2022.
CROSBY, M. et al. Blockchain Technology: Beyond Bitcoin. Applied Innovation Review, v. 2, p. 6–10, 2016.
DWIVEDI, A. D. et al. Security and Privacy of IoT Data in Healthcare: A Review. Computer Communications, v. 153, p. 313–332, 2021.
FERNANDES, E.; JUN, S.; PRASAD, R. Security implications of smart medical devices. Communications of the ACM, v. 59, n. 10, p. 24–26, 2016.
FERREIRA, L. M.; SOUZA, T. R. Conformidade Legal em Sistemas de Saúde Digital: Uma Análise da LGPD e HIPAA. Revista de Direito e Tecnologia, v. 9, n. 2, p. 88–105, 2023.
GENTRY, C. Fully Homomorphic Encryption Using Ideal Lattices. In: ACM Symposium on Theory of Computing. Bethesda: ACM, 2009. p. 169–178.
HHS – U.S. Department of Health and Human Services. Health Insurance Portability and Accountability Act of 1996 (HIPAA). Disponível em: https://www.hhs.gov/hipaa. Acesso em: 23 out. 2025.
ISLAM, S. K. H. et al. Security and privacy issues in wireless sensor networks for healthcare applications. Journal of Medical Systems, v. 39, n. 1, p. 1–8, 2015.
ISO. ISO/IEC 27001:2022 – Information Security Management Systems. Geneva: International Organization for Standardization, 2022.
KOBLITZ, N. Elliptic Curve Cryptosystems. Mathematics of Computation, v. 48, n. 177, p. 203–209, 1987.
KSHETRI, N. Blockchain’s Roles in Meeting Key Supply Chain Management Objectives. International Journal of Information Management, v. 39, p. 80–89, 2017.
KUMAR, A.; PATEL, S. Privacy-Preserving Data Analytics in Healthcare Using Homomorphic Encryption. Journal of Biomedical Informatics, v. 142, p. 104383, 2024.
NAKAMOTO, S. Bitcoin: A Peer-to-Peer Electronic Cash System. 2008. Disponível em: https://bitcoin.org/bitcoin.pdf. Acesso em: 25 out. 2025.
RAY, P. Home Health Hub Internet of Things (H3IoT): An architectural framework for monitoring health of elderly people. IEEE International Conference on Information Technology, Electronics and Mobile Communication, p. 1–6, 2016.
SARKER, I. H.; ALZAMIL, Z.; HOQUE, M. M. AI-Driven Cybersecurity: Threat Detection and Mitigation in IoT-Based Smart Healthcare Systems. Sensors, v. 21, n. 23, p. 1–22, 2021.
SICARI, S. et al. Security, Privacy and Trust in Internet of Things: The Road Ahead. Computer Networks, v. 76, p. 146–164, 2015.
SINGH, R.; KUMAR, N. Lightweight Cryptography for IoT Healthcare Devices: A Comparative Study. Journal of Network and Computer Applications, v. 205, p. 103408, 2023.
TOPOL, E. Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. New York: Basic Books, 2019.
WHO – World Health Organization. Ethics and Governance of Artificial Intelligence for Health. Geneva: WHO, 2021.
XU, X.; WEBBER, M.; ZHENG, Z. Smart Healthcare Blockchain: A Decentralized Architecture for Patient Monitoring. IEEE Access, v. 7, p. 102019–102030, 2019.
ZHANG, Y. et al. Blockchain-Based Secure Data Sharing for Internet of Medical Things. IEEE Internet of Things Journal, v. 8, n. 2, p. 1202–1213, 2021.
ZHENG, Z. et al. An Overview of Blockchain Technology: Architecture, Consensus, and Future Trends. In: IEEE International Congress on Big Data. Honolulu: IEEE, 2018. p. 557–564.
ZHOU, J. et al. Deep Learning for Cybersecurity in IoT Healthcare: A Survey. IEEE Transactions on Industrial Informatics, v. 18, n. 3, p. 1802–1814, 2022.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
