An Adaptive Hybrid Encryption Scheme for Data Compliance in Multi-Source Supervision Environments: A Case Study of Hainan Free Trade Port

As the global digital economy expands, cross-border data transmission confronts the dual imperatives of high-level confidentiality and stringent multi-party regulatory compliance. Existing hybrid and Attribute-Based Encryption (ABE) paradigms frequently fail to reconcile dynamic multi-source supervision with computational efficiency. Traditional multi-authority approaches typically suffer from linear ciphertext expansion and heavy terminal decryption overheads. To bridge this gap, this paper proposes an Adaptive Hybrid Encryption scheme for Multi-Source supervision environments (AHE-MS), contextualized within the Hainan Free Trade Port. Our core theoretical contribution is a zero-knowledge compliance verification architecture. To achieve data-blind compliance verification, we embed regulatory policies into a Linear Secret Sharing Scheme (LSSS) matrix and introduce an aggregate token mechanism rooted in group homomorphisms. By constraining mandatory regulatory attributes to root-level AND gates, AHE-MS allows regulators to append compliance credentials without ciphertext expansion, strictly maintaining an \(\:O\left(1\right)\) communication overhead. Crucially, the regulatory pre-verification offloads pairing computations, significantly alleviating the terminal decryption burden. To ensure secure and practical deployment in high-throughput pipelines, the system integrates a sensitivity-driven KEM/DEM architecture with authenticated downgrade protection. Theoretical analysis proves AHE-MS achieves IND-CPA security under the standard model. Extensive simulations demonstrate that, during multi-source interventions, AHE-MS accelerates terminal decryption by up to 23.8% compared to classic CP-ABE.