TeleZK-L2: A Scalable zk-SNARK Framework for Privacy-Preserving Telehealth Data Verification on Layer-2 Blockchain

Radhakrishnan Delhibabu^*Prabhavathi Jayaraman

• VIT University, Vellore, India

In the contemporary digital health landscape, securing personal health data against unauthorized access while ensuring its verifiability has become 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. The rapid proliferation of telehealth platforms and the Internet of Medical Things (IoMT) necessitates scalable mechanisms to authenticate high-volume health data streams without compromising patient confidentiality. Existing Layer-1 blockchain solutions suffer from prohibitive gas costs and high latency, rendering them unsuitable for real-time monitoring. To address these limitations, 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 framework introduces a Distributed Prover Network (DPN) to parallelize heavy cryptographic computations and utilizes Optimistic Proof Aggregation to minimize on-chain data footprints. This architecture provides the technical privacy guarantees necessary to support adherence to HIPAA and GDPR data minimization mandates, while maintaining cryptographic soundness. By anchoring the verification logic on the Polygon zkEVM, TeleZK-L2 ensures high throughput and low-cost settlement. 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 and reduces on-chain verification costs by approximately 52%. Furthermore, the system maintains constant-time verification complexity regardless of the batch size, highlighting its potential for large-scale deployment in national telehealth infrastructures.