Contract defect detection method based on intelligent contract knowledge graph

Abstract

The invention discloses a contract defect detection method based on an intelligent contract knowledge graph. The contract defect detection method is mainly used for detecting code defects of an intelligent contract written by a Solidiity language on an Ethereum platform. The code defects of the smart contract refer to errors, faults or vulnerabilities in the smart contract, which may cause incorrect or accidental execution of the smart contract. The defect mode of the smart contract is defined by analyzing the defect of the smart contract. For a to-be-detected smart contract, the source code of the smart contract is analyzed based on Solidity grammar, and a smart contract abstract syntax tree is generated; basic knowledge entities and relationships thereof of the smart contract are obtained through an abstract syntax tree, so that a smart contract knowledge graph is constructed, and the smart contract knowledge graph is stored in an RDF triple database; and on the basis of the intelligent contract knowledge graph, reasoning query is performed by applying a knowledge graph query statement, the intelligent contract is matched with a defect mode, and defects and positions of the intelligent contract are detected.

Description

technical field [0001] The invention belongs to the field of smart contract defect detection of a block chain system, and relates to a contract defect detection method based on a smart contract knowledge map. Background technique [0002] Blockchain, as a distributed public ledger technology in a peer-to-peer network, is widely used in various fields. However, there are still security issues in the smart contract itself, which affects the further promotion and use of blockchain technology. Defects in the smart contract itself, calls between contracts, etc. are all important factors that affect the security of the contract. Before the smart contract goes online, it is necessary to conduct comprehensive and in-depth defect detection on the smart contract, fully analyze potential security threats, avoid defects as much as possible, and ensure the logical correctness of the smart contract code and the security of the assets involved with a higher standard. [0003] At present,...

AI Technical Summary

Problems solved by technology

The formal verification method of theorem proof uses a general method to construct code patterns and theorems to prove the security of smart contracts. It is difficult to fully automate the entire verification process, so a lot of manual work is required to build proofs and analysis of smart contracts

The advantage of the model checking method is that it has a high degree of automation. Even if only a partial description of the contract is given, useful information about the correctness of the known part can be provided by searching. The disadvantage of this method is that there is a state explosion problem. The model checking algorithm As the number of states in the model checking tool increases, the computation time will explode and the resource consumption on the computation space will expand

The fuzz testing method detects the contract by monitoring the dynamic running process of the smart contract, so it can detect the real loopholes of the contract more accurately. The disadvantage of this method is that the test cases are randomly generated, which can only cover part of the system behavior, and the path coverage is limited.

Images