@Article{cmc.2025.062324,
AUTHOR = {Shenjian Xiao, Xiaoli Qin, Yanzhao Tian, Zhongkai Dang},
TITLE = {Blockchain-Based Framework for Secure Sharing of Cross-Border Trade Data},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {83},
YEAR = {2025},
NUMBER = {2},
PAGES = {2351--2373},
URL = {http://www.techscience.com/cmc/v83n2/60576},
ISSN = {1546-2226},
ABSTRACT = {The advent of the digital age has consistently provided impetus for facilitating global trade, as evidenced by the numerous customs clearance documents and participants involved in the international trade process, including enterprises, agents, and government departments. However, the urgent issue that requires immediate attention is how to achieve secure and efficient cross-border data sharing among these government departments and enterprises in complex trade processes. In addressing this need, this paper proposes a data exchange architecture employing Multi-Authority Attribute-Based Encryption (MA-ABE) in combination with blockchain technology. This scheme supports proxy decryption, attribute revocation, and policy update, while allowing each participating entity to manage their keys autonomously, ensuring system security and enhancing trust among participants. In order to enhance system decentralization, a mechanism has been designed in the architecture where multiple institutions interact with smart contracts and jointly participate in the generation of public parameters. Integration with the multi-party process execution engine Caterpillar has been shown to boost the transparency of cross-border information flow and cooperation between different organizations. The scheme ensures the auditability of data access control information and the visualization of on-chain data sharing. The MA-ABE scheme is statically secure under the q-Decisional Parallel Bilinear Diffie-Hellman Exponent (q-DPBDHE2) assumption in the random oracle model, and can resist ciphertext rollback attacks to achieve true backward and forward security. Theoretical analysis and experimental results demonstrate the appropriateness of the scheme for cross-border data collaboration between different institutions.},
DOI = {10.32604/cmc.2025.062324}
}