Secure And Private Analytics Of Healthcare Records In Multi-Tenant Cloud Environments Using Blockchain

Abstract

The growing volume of digital healthcare data and increasing incidents of data breaches have intensified concerns regarding the protection of sensitive patient information. Healthcare analytics systems must therefore balance privacy preservation with the ability to generate meaningful insights. This paper presents a secure framework that integrates privacy-preserving mechanisms, zero-knowledge proofs (zk-SNARKs), blockchain technology, and a multi-tenant cloud architecture to address these challenges. The proposed approach safeguards healthcare records during analytical computations by applying advanced cryptographic techniques, enabling verification without revealing underlying data.Within the framework, anonymized healthcare datasets are processed by a privacy-preserving analytics engine that generates zk-SNARK proofs to validate computations. These proofs are recorded on a blockchain network, creating a transparent and tamper-resistant ledger that enhances trust and security in healthcare data transactions. Such a mechanism is particularly beneficial in telemedicine scenarios, where secure sharing and processing of patient information are critical. The implementation of the proposed model in a telemedicine application demonstrates its scalability, reliability, and effectiveness. Overall, the framework provides a practical solution for secure healthcare analytics while maintaining strict privacy guarantees.