.png){kind=icon}
返回
An Efficient Smart Contract Vulnerability Detector Based on Semantic Contract Graphs Using Approximate Graph Matching
.png){kind=icon}
PRE
AI
DOI：10.1109/JIOT.2023.3294496.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The Internet of Things (IoT) has become a focus of information infrastructure development in recent years. The smart blockchain can provide various solutions for trust, security, and privacy (TSP) challenges to protect IoT data, and smart contracts are the foundation of blockchain intelligence, and greatly enhance the ability of smart blockchain to solve TSP problems. So, the security of smart contracts must be addressed. We propose an efficient smart contract vulnerability detector to improve the safety of smart contracts. It comprises a graph extraction method and a complete vulnerability detection process. The graph extraction method consists of vulnerability pattern extraction and a graph generation process. The vulnerability detection process first uses the approximate graph matching algorithm to select representative SCGraphs from the data set to build vulnerability SCGraph libraries. Second, determine whether the contract contains vulnerabilities by calculating the similarity between the SCGraphs generated from the contracts to be detected and the SCGraphs in the vulnerability library. Experiments show that our approach achieves an inspiring high detection rate and is the fastest among existing vulnerability detection tools, which indicates that it can provide good vulnerability detection for smart contracts.
Keyword:
Approximate graph matching
semantic contract graph
smart blockchain
smart contracts
vulnerability
期刊
IF:
8.9
论文数:
1.4W
被引数:
7.8W
机构
引用论文
.png){kind=icon}
Ultrafast Absorption Changes of the Lhcii Carotenoids upon Selective Excitation of the Chlorophylls
PREAI
分享收藏Combining Graph Neural Networks With Expert Knowledge for Smart Contract Vulnerability Detection结合图神经网络和专家知识的智能合约漏洞检测
OAAI
OAAI分享收藏Energy-Efficient Smart Routing Based on Link Correlation Mining for Wireless Edge Computing in IoT基于链路关联挖掘的物联网无线边缘计算节能智能路由
PREAI
分享收藏分享收藏A demonstration of GeoSpark: A cluster computing framework for processing big spatial dataGeoSpark的演示: 用于处理大空间数据的集群计算框架
PREAI
分享收藏Hierarchical Adversarial Attacks Against Graph-Neural-Network-Based IoT Network Intrusion Detection System基于图神经网络的物联网网络入侵检测系统分层对抗攻击OAAI
OAAI分享收藏
查看更多内容