Welcome to the image-malware-detection-model project! This application helps you detect malware embedded in images using advanced techniques. No programming skills are needed to get started. Follow these simple steps to download and run the software.
- Click the link above to visit the Releases page.
- Look for the latest version of the application.
- Download the appropriate file for your operating system (e.g., Windows, macOS, Linux).
- Once downloaded, locate the file in your downloads folder.
- Double-click the file to start the installation process.
- Follow the on-screen instructions to complete the installation.
To ensure smooth operation, please check that your system meets the following requirements:
- Operating System: Windows 10, macOS 10.14 or later, or a modern Linux distribution.
- RAM: At least 4 GB of RAM.
- Storage: Minimum of 1 GB of free disk space.
- Python: Installed on your system (version 3.6 or later).
If you need help installing Python, you can find instructions at the Python official website.
Using this application is straightforward. Once installed, follow these steps:
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Open the Application: Find the application icon on your desktop or in the programs menu. Double-click to launch it.
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Upload an Image: Click the "Upload" button to select an image file from your computer. The application supports common formats like JPEG, PNG, and BMP.
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Run the Detection: After uploading the image, click the "Run Detection" button. The model will analyze the image to check for potential malware.
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View Results: Once processing is complete, results will appear on the screen. The application will display whether malware was detected and provide details for further analysis.
- Advanced Machine Learning Models: The application uses Convolutional Neural Networks (CNN), ResNet18, and EfficientNet-B0 for accurate malware classification.
- Model Comparison: Evaluate different models side-by-side to understand their effectiveness.
- Visualization Tools: View graphs and metrics that illustrate the results of your scans.
- User-Friendly Interface: Easy navigation makes it simple for anyone to use, regardless of technical background.
After running the detection, the application provides a summary of findings with the following information:
- Malware Status: Indicates if malware is detected (Yes/No).
- Confidence Level: A percentage score that shows how certain the model is about its findings.
- Classification Type: Learn more about the type of malware detected, if applicable.
- Additional Information: Access links for further reading or action if malware is found.
Join our community to stay updated on new features and discuss best practices:
- Issues: Report bugs or request features on the GitHub Issues page.
- Discussions: Engage with other users to share insights or ask for help.
- Documentation: Check the README files for more extensive guidance and FAQs.
This project is licensed under the MIT License. You may use it freely, but please adhere to the license terms.
- Always run checks on images from untrusted sources.
- It is a good idea to update the software regularly to benefit from improvements and new features.
- Future versions may include enhancements and new models for better accuracy.
For more information, visit the official Releases page to download the latest version.