@inproceedings{556469553fc94c3b981c77b10357ff5c,
title = "Business Compliance Detection of Smart Contracts in Electricity and Carbon Trading Scenarios",
abstract = "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.",
keywords = "Blockchain, Business Compliance, Electricity and Carbon Trading, LLMs, Smart Contract",
author = "Yin Wu and Haijun Wang and Yuanhui Zhang and Xitao Li and Hao Wu and Ming Fan and Ting Liu",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 35th IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2024 ; Conference date: 28-10-2024 Through 31-10-2024",
year = "2024",
doi = "10.1109/ISSREW63542.2024.00074",
language = "英语",
series = "Proceedings - 2024 IEEE 35th International Symposium on Software Reliability Engineering Workshops, ISSREW 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "177--178",
booktitle = "Proceedings - 2024 IEEE 35th International Symposium on Software Reliability Engineering Workshops, ISSREW 2024",
}