TeleZK-L2: a scalable zk-SNARK framework for privacy-preserving telehealth data verification on Layer-2 blockchain

Abstract

Introduction In the contemporary digital health landscape, securing personal health data against unauthorized access while ensuring its verifiability is a paramount challenge. A critical conflict exists between the transparency required for data verification and the privacy mandated by global regulations such as HIPAA and GDPR. Existing Layer-1 blockchain solutions suffer from prohibitive gas costs and high latency, rendering them unsuitable for real-time monitoring of high-volume health data streams. Methods This paper proposes TeleZK-L2, a novel framework that synergizes distributed Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge (zk-SNARKs) with Layer-2 scaling solutions. The architecture introduces a Distributed Prover Network (DPN) to parallelize heavy cryptographic computations and utilizes Optimistic Proof Aggregation to minimize on-chain data footprints. The verification logic is anchored on the Polygon zkEVM to ensure high throughput and low-cost settlement. Results Extensive simulations on a 16-node high-performance cluster demonstrate that TeleZK-L2 generates proofs at a rate 40% faster than the standard Groth16 baseline. Furthermore, the framework reduces on-chain verification costs by approximately 52%. The system maintains constant-time verification complexity regardless of batch size, achieving a peak throughput of 260 TPS. Discussion TeleZK-L2 provides the technical privacy guarantees necessary to support adherence to HIPAA and GDPR data minimization mandates while maintaining cryptographic soundness. By resolving the "Scalability-Privacy Trilemma," this framework demonstrates significant potential for large-scale deployment in national telehealth infrastructures and remote patient monitoring ecosystems.