Scalable Approach for Zero-Knowledge Proofs (ZKP): Reducing Proving Time with KZG Commitments

Zero-Knowledge Proofs (ZKP) provide strong data privacy and rely on the principle of proving a statement without revealing the underlying data. However, the ZK-SNARK system has a scalability problem while generating proofs. Systems like PLONK take longer to generate a proof with increasing size of the input data. EHR(Electronic Health Records) may present a short proving time but large size data sine when they contain images and genomics it could take more time to generate a proof. ZK-Rollup systems provide scalability by batching the transactions in off-chain mode; however, they also suffer from longer proving time with large data. In this paper, we propose an approach to generate KZG commitments from healthcare FHIR records and then use these values to generate single validity ZKP. In this way, we can not only reduce the proving time, but also ensure data integrity and data correctness.