Integrating Homomorphic Encryption with Blockchain Technology for Machine Learning Applications
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ournal of Machine and Computing
Abstract
Leveraging cutting-edge technology like blockchain and machine intelligence, smart healthcare systems have
emerged as a potential strategy for enhancing healthcare services. In order to secure health data, this study offers a unique
design and analysis of a smart healthcare system that applies blockchain technique and the paillier homomorphic encryption
algorithm in addition to a machine learning algorithm to detect cardiological disease. The suggested method seeks to solve
the problems with predictive analytics and safe health data exchange in the medical field. Sensitive information is encrypted
during transmission and storage using the Paillier Homomorphic Encryption technique, guaranteeing its confidentiality. By
providing traceability and accountability in data access and sharing, blockchain technology is used to construct a safe and
transparent record of health transactions. In addition, a machine learning algorithm is used to forecast cardiac illness based
on the encrypted data, giving medical practitioners insightful information to help them make judgments. The integration of
these technologies and their advantages in improving healthcare services are highlighted in the discussion of the proposed
scheme's constructional and operational specification section. Simulation experiments are used to assess the suggested
method’s efficiency and reflect its efficacy in terms of data security, detection accurateness, and computing proficiency.
Comparing the integrated approach to conventional approaches, the results demonstrate a considerable improvement in
prediction accuracy and security of health data. To sum up, the suggested smart healthcare system provides a thorough
approach to guaranteeing the security of patient data and enhancing predictive analytics in the medical field. Machine
learning, blockchain technology, and Paillier homomorphic encryption are all integrated into it, which shows promise for
improving healthcare services and developing the field of smart healthcare systems.
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Citation
Das, Kajaree, and Rabi Narayan Behera. "A survey on machine learning: concept, algorithms and applications." International Journal of Innovative Research in Computer and Communication Engineering 5.2 (2017): 1301-1309.
