A Systematic Literature Review on Automated Software Vulnerability Detection Using Machine Learning
N Shiri Harzevili, A Boaye Belle, J Wang… - ACM Computing …, 2024 - dl.acm.org
In recent years, numerous Machine Learning (ML) models, including Deep Learning (DL)
and classic ML models, have been developed to detect software vulnerabilities. However …
and classic ML models, have been developed to detect software vulnerabilities. However …
[HTML][HTML] To healthier ethereum: A comprehensive and iterative smart contract weakness enumeration
Abstract test With the increasing popularity of cryptocurrencies and blockchain technology,
smart contracts have become a prominent feature in developing decentralized applications …
smart contracts have become a prominent feature in developing decentralized applications …
Cobra: Interaction-aware bytecode-level vulnerability detector for smart contracts
The detection of vulnerabilities in smart contracts remains a significant challenge. While
numerous tools are available for analyzing smart contracts in source code, only about 1.79 …
numerous tools are available for analyzing smart contracts in source code, only about 1.79 …
A Survey on Security Analysis Methods of Smart Contracts
H Zhu, L Yang, L Wang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Smart contracts have gained extensive adoption across diverse industries, including
finance, supply chain, and the Internet of Things. Nevertheless, the surge in security …
finance, supply chain, and the Internet of Things. Nevertheless, the surge in security …
A survey on automated software vulnerability detection using machine learning and deep learning
Software vulnerability detection is critical in software security because it identifies potential
bugs in software systems, enabling immediate remediation and mitigation measures to be …
bugs in software systems, enabling immediate remediation and mitigation measures to be …
Fine-grained smart contract vulnerability detection by heterogeneous code feature learning and automated dataset construction
Context: Recently, several deep learning based smart contract vulnerability detection
approaches have been proposed. However, challenges still exist in applying deep learning …
approaches have been proposed. However, challenges still exist in applying deep learning …
Software Vulnerability Detection Using Informed Code Graph Pruning
pruning methods that can be used to reduce graph size to manageable levels by removing
information irrelevant to vulnerabilities, while preserving relevant information. We present …
information irrelevant to vulnerabilities, while preserving relevant information. We present …
Vulnsense: efficient vulnerability detection in ethereum smart contracts by multimodal learning with graph neural network and language model
With the proliferation of Ethereum smart contracts comes an increasing concern for security
vulnerabilities that could lead to significant financial losses. Current methods for detecting …
vulnerabilities that could lead to significant financial losses. Current methods for detecting …
Large-Scale Study of Vulnerability Scanners for Ethereum Smart Contracts
C Sendner, L Petzi, J Stang… - 2024 IEEE Symposium on …, 2024 - computer.org
Ethereum smart contracts, which are autonomous decentralized applications on the
blockchain that manage assets often exceeding millions of dollars, have become primary …
blockchain that manage assets often exceeding millions of dollars, have become primary …
Vulnerability Detection in Smart Contracts: A Comprehensive Survey
C De Baets, B Suleiman, A Chitizadeh… - arXiv preprint arXiv …, 2024 - arxiv.org
In the growing field of blockchain technology, smart contracts exist as transformative digital
agreements that execute transactions autonomously in decentralised networks. However …
agreements that execute transactions autonomously in decentralised networks. However …