Combine sliced joint graph with graph neural networks for smart contract vulnerability detection-Reference-Cited by-同舟云学术

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Combine sliced joint graph with graph neural networks for smart contract vulnerability detection

Published:2023-01 Issue: Volume:195 Page:111550
ISSN:0164-1212
Container-title:Journal of Systems and Software
language:en
Short-container-title:Journal of Systems and Software

Author:

Cai Jie,Li Bin,Zhang Jiale^ORCID,Sun Xiaobing^ORCID,Chen Bing

Publisher

Elsevier BV

Subject

Hardware and Architecture,Information Systems,Software

Reference50 articles.

1. SMT-based verification of solidity smart contracts;Alt,2018

2. Enriching word vectors with subword information;Bojanowski;Trans. Assoc. Comput. Linguist.,2017

3. Ethainter: a smart contract security analyzer for composite vulnerabilities;Brent,2020

4. Vandal: A scalable security analysis framework for smart contracts;Brent,2018

5. The story of the DAO—Its history and consequences;Falkon,2017

Cited by 24 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. ReenRepair: Automatic and semantic equivalent repair of reentrancy in smart contracts;Journal of Systems and Software;2024-10

2. A vulnerability detection framework with enhanced graph feature learning;Journal of Systems and Software;2024-10

3. Empirical Study of Move Smart Contract Security: Introducing MoveScan for Enhanced Analysis;Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis;2024-09-11

4. Interpretable software estimation with graph neural networks and orthogonal array tunning method;Information Processing & Management;2024-09

5. SGDL: Smart contract vulnerability generation via deep learning;Journal of Software: Evolution and Process;2024-07-20

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