SECURE AND PRIVATE ANALYTICS OF HEALTHCARE RECORDS IN MULTI-TENANT CLOUD ENVIRONMENTS USING BLOCKCHAIN

Abstract

Given the sensitivity of personal health information and the rising prevalence of data breaches, healthcare analytics faces a significant challenge in ensuring the privacy of sensitive data while simultaneously providing valuable insights. By incorporating privacy-preserving parameters, zero-knowledge proofs (zkSNARKs), blockchain technology, and a multi-tenant cloud environment, the secure framework presented in this paper addresses these issues. The framework ensures that healthcare records remain protected during analytics computations without exposing raw data by employing cuttingedge cryptographic methods, particularly zk-SNARKs. In order to validate computations, the privacypreserving analytics engine makes use of anonymized healthcare records and generates zk-SNARKs. When these proofs are incorporated into a blockchain network, they produce a transparent, tamper-proof ledger that guarantees safe healthcare transactions. This strategy is absolutely necessary in circumstances like telemedicine, where secure data sharing and computation are of the utmost importance. By demonstrating its application in a telemedicine app, the framework provides a scalable and secure solution to a pressing issue, demonstrating its practical significance in healthcare analytics.