Business Compliance Detection of Smart Contracts in Electricity and Carbon Trading Scenarios
Business compliance in smart contracts for blockchain-based electricity and carbon trading (B-ECT) remains unexplored. We propose an automated Business Compliance Detection tool for smart contracts (BCDetection ) in B-ECT to address this gap. Our innovation encompasses the creation of a benchmark dataset containing both compliant and non-compliant smart contracts, coupled with the deployment of Agent-based Large Language Models (LLMs) to align smart contract codes with prevailing business regulations. The BCDetection tool employs a structured agent for compliance verification, including pre-judgment, feature extraction, fine-grained feature alignment, and consistency judgment. A case study demonstrates its effectiveness. As the field evolves, our approach shows promise for enhancing security and compliance.
Authors
- Yin Wu (ORCID: https://orcid.org/0000-0003-3211-2886)
- Haijun Wang (ORCID: https://orcid.org/0000-0003-0119-3804)
- Ming Yu Fan (ORCID: https://orcid.org/0000-0002-9327-0987)
- Hao Wu (ORCID: https://orcid.org/0000-0001-8448-5284)
- Yuanhui Zhang (ORCID: https://orcid.org/0000-0002-6021-0582)
- Ting Liu (ORCID: https://orcid.org/0000-0002-7600-0934)
- Xiao Hui Li
Institutions
- Xi'an Jiaotong University (CN)
Publication Details
- Published
- 2024-10-28
- DOI
- https://doi.org/10.1109/issrew63542.2024.00074
- Citations
- 3
- Primary Topic
- FinTech, Crowdfunding, Digital Finance
- Type
- article
- Field-Weighted Citation Impact
- 1.59
Funders
- National Natural Science Foundation of China
- Innovation Fund
- Research and Development