A Lightweight Privacy‐Preserving Audit Framework Based on Blockchain and Hybrid Encryption

This study investigates an audit data privacy protection mechanism based on blockchain technology and constructs a secure and efficient computational model. The system is designed to support practical domains such as medical record systems and financial audit platforms, ensuring data integrity, traceability, and confidentiality. Leveraging a distributed ledger and optimized consensus mechanism, the model automates data sharing and audit processes through smart contracts. A hybrid encryption approach is proposed, integrating RSA algorithm with chaos theory to enhance encryption complexity and randomness. Experimental results—conducted on real‐world medical audit data—demonstrate that, compared to baseline methods, the proposed scheme improves privacy protection by up to 50%, increases ciphertext complexity by 45%, and reduces encryption and verification time by approximately 20 s. The system also supports up to 500 concurrent users with a throughput of 583.49 requests/s, indicating strong scalability and efficiency.