ZkHybridChain: ultra-efficient cross-border credit recognition

Abstract

Background Cross-border credit recognition in Sino-Foreign Cooperative Education (SFCE) suffers from data fragmentation, regulatory conflicts (e.g., GDPR vs. China’s Data Security Law), and low efficiency. Objective This paper proposes ZkHybridChain, a dual-layer blockchain credit bank (BCB) framework to resolve the privacy-compliance-efficiency trilemma. Methods The hybrid architecture integrates Polygon zkEVM (public credential hashing) and Hyperledger Fabric (private raw data storage). Zero-Knowledge Proofs (ZKP) and three-tiered smart contracts enable automated credit conversion (ECTS↔CNQF) and privacy-preserving verification. Results Experiments on 10,000 SFCE records show 58% efficiency gain (full lifecycle from ∼1,200 s to <9 s), cross-border latency <9 s, throughput up to 1,620 TPS, and ZKP verification latency 135 ms (93.7% success rate). Conclusion ZkHybridChain provides a scalable, GDPR/DSL-compliant solution for global education trust networks. Future work includes post-quantum cryptography and lightweight client protocols.