Intelligent contract reentrancy vulnerability detection method based on graph neural network

Abstract

The invention discloses an intelligent contract reentrancy vulnerability detection method based on a graph neural network, which realizes intelligent contract reentrancy vulnerability detection through optimized graph neural network training and learning, and specifically comprises the following steps: collecting an intelligent contract source code data set; extracting and constructing a corresponding graph structure model by the smart contract source code; standardizing the graph structure; constructing a graph neural network of the time message flow; and inputting the standardized intelligent contract graph structure data set, training an intelligent contract reentrant vulnerability detection model, and realizing intelligent contract reentrant vulnerability detection through the model. The static source code is converted into a message flow graph structure with a time sequence, reentrant and non-reentrant labels can be automatically output through the training model, the vulnerability detection accuracy is improved, a new method thought is provided for intelligent contract vulnerability detection, and the method has good practical value.

Description

technical field [0001] The invention belongs to the technical field of block chain smart contract security loophole detection, and in particular relates to a method for detecting reentrant loopholes of smart contracts based on a graph neural network. Background technique [0002] Smart contract is one of the core technologies of blockchain, it is the consensus rule in multi-party participation scenarios, and smart contract is the center of value transmission. The reason why security issues have become more important than ever after the emergence of the blockchain is because smart contracts realize a kind of value transfer. Every number on the blockchain is a value, and the digital changes caused by each loophole are behind it. Huge loss of value. [0003] In June 2016, The DAO security breach resulted in a loss of 50 million US dollars; in July 2017, the Parity multi-signature wallet had two security breaches, resulting in a loss of 30 million US dollars and 152 million US ...

AI Technical Summary

Problems solved by technology

[0003] In June 2016, The DAO security breach resulted in a loss of US$50 million; in July 2017, the Parity multi-signature wallet had two security breaches, resulting in a loss of US$30 million and US$152 million respectively

Although methods have been proposed to detect various vulnerabilities in smart contracts, there is still a lack of in-depth research on reentrancy vulnerabilities in specific domains.

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