A Blockchain-Based, Efficient, and Privacy-Preserving Data Exchange System for mHealthcare that Includes Trust Authentication
Abstract:
The
mobile healthcare (mHealthcare) paradigm provides promise to
enhance the delivery of healthcare services through remote diagnostics and
medical data interchange. But problems like unapproved access and data leaks
continue. Although there are still problems, attribute-based encryption (ABE)
is a useful cryptographic method for protecting data exchange in mHealthcare. To address these
problems, this study provides an effective data sharing strategy that also
protects privacy. The mHealthcare service users activity has been
monitored for malicious analysis in which the authentication of the users is
analysed using convolutional reinforcement fuzzy neural network. the trained
and classified output gives security analysis based on healthcare data
modelling then the network privacy is enhanced. In order to protect user
privacy, it hides a portion of the access policy, adds an offline method for
generating keys and encrypting data in mHealthcare, and uses blockchain
technology to provide decentralized, reliable verification of data access
rights. The enhanced security and efficiency of the method are confirmed by
security proofs and experimental outcomes. Proposed technique attained detection accuracy 96%, data privacy analysis
of 94%, recall of 90%, RMSE of 60% based on mHealthcare dataset
analysis.
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