Abstract:
With the rapid development of blockchain technology, the use of decentralized applications (DApps) has experienced significant growth. However, current testing methods fo...Show MoreMetadata
Abstract:
With the rapid development of blockchain technology, the use of decentralized applications (DApps) has experienced significant growth. However, current testing methods for DApps primarily focus on testing the smart contracts on the blockchain, which are the foundation of DApps, but lack a comprehensive approach to effectively detect off-chain abnormal states. To address this issue, this paper proposes a generic abnormal state detection model based on off-chain transaction data. The model leverages the DApp program code logic to set up test oracles to analyze off-chain transaction data. Experimental results demonstrate that the model achieves high accuracy in detecting off-chain abnormal states, with a prediction accuracy as high as 96.3%. Furthermore, a comparison with other related vulnerability detection methods shows the advantages of the proposed approach.
Published in: 2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
Date of Conference: 01-03 November 2023
Date Added to IEEE Xplore: 29 May 2024
ISBN Information: