At present, the most commonly used method for detecting software vulnerabilities is static analysis. Most of the related technologies work based on rules or ...
Apr 29, 2021 · In [15], the authors present a vulnerability detection system VulDeePecker based on deep learning.
At present, the most commonly used method for detecting software vulnerabilities is static analysis. Most of the related technologies work based on rules or ...
The application of neural network for software vulnerability detection: a review · An Automatic Source Code Vulnerability Detection Approach Based on KELM.
At present, the most commonly used method for detecting software vulnerabilities is static analysis. Most of the related technologies work based on rules or ...
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What are the techniques for identifying computer vulnerabilities?
Can deep learning models learn the vulnerable patterns for vulnerability detection?
This paper collects two datasets from the programs involving 126 types of vulnerabilities and conducts the first comparative study to quantitatively ...
The process of deep learning-based vulnerability detection has six steps: generating code gadgets (Step I), generating ground truth labels for code gadgets ( ...
Mar 28, 2024 · This study presents a novel deep learning-based vulnerability detection system for Java code. Leveraging hybrid feature extraction through graph ...
A Comparative Study of Neural. Network Techniques for Automatic Software Vulnerability Detection. In 2020 International Symposium on Theoretical Aspects of ...
A comparative study of neural network techniques for automatic software vulnerability detection ... Neural Network for Software Vulnerability Identification. no ...