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A cognitive approach for blockchain-based cryptographic curve hash signature (BC-CCHS) technique to secure healthcare data in Data Lake
In today's digital world, information is exchanged among various sources, and it is expected that each interaction or transaction among the sources must be reliable and secure. In these circumstances, blockchain technology can be applied to ensure healthcare data security in an efficient way. B...
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Published in: | Soft computing (Berlin, Germany) Germany), 2021-11, p.1-15 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that cite this one |
Online Access: | Get full text |
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Summary: | In today's digital world, information is exchanged among various sources, and it is expected that each interaction or transaction among the sources must be reliable and secure. In these circumstances, blockchain technology can be applied to ensure healthcare data security in an efficient way. Blockchain is an ordered list of records linked together through a chain of blocks in a distributed ledger. It is a decentralized and tamper-proof database system. It can be used to store the medical records of patients and play a vital role in healthcare to maintain and share medical data securely. At present, many scholars are focusing on the privacy and security in electronic health record (EHR) sharing based on blockchain technology. But still, the security of health data plays a significant challenge. A Cognitive Approach blockchain-based cryptographic curve hash signature (BC-CCHS) technique is proposed to secure patients' medical records and share their personal health data safely and conveniently. The proposed approach is carried out in the Hyperledger framework. Here, several phases like registration, authentication, uploading, and requesting are involved in enhancing the security mechanism. The proposed methodology is experimentally tested and validated with the existing techniques regarding encryption time, decryption time, throughput, delay, and overall processing time. |
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ISSN: | 1432-7643 1433-7479 |
DOI: | 10.1007/s00500-021-06513-7 |