|
As Ethereum emerges as a leading platform in blockchain technology, it increasingly faces security threats, particularly targeting smart contracts and decentralized applications (DApps). Current transaction analysis methods, such as dynamic taint analysis based on transaction tracing, are effective in specific scenarios but often fall short in handling complex logical vulnerabilities. Addressing these challenges, this study introduces a novel method for detecting attack transactions in Ethereum, focusing on the analysis of asset transfer behaviors between transaction initiators and interacting contract accounts. The innovation of this approach lies in its perspective of asset transfer, offering a fresh vantage point for identifying potential attack patterns. In the experimental phase, the method demonstrated effectiveness on existing datasets, albeit with the possibility of false positives in more complex scenarios. Overall, this study provides a new perspective in the field of Ethereum security research and offers valuable insights for enhancing the accuracy and efficiency of blockchain transaction security analysis.
|
