Vul2image: A quick image-inspired and CNN-based vulnerability detection system

Key Points

• Vulnerability detection accuracy reached 95% with the CNN approach, significantly optimizing the process.
• The system employs convolutional neural networks (CNN) to analyze images for vulnerabilities.
• Observational analysis utilizes a dataset of 100 software applications for training and testing the model.
• This method may enable quicker identification of vulnerabilities, suggesting potential for broader applications.