https://github.com/zpettry/ai-deep-learning-for-phishing-url-detection

AI: Deep Learning for Phishing URL Detection
https://github.com/zpettry/ai-deep-learning-for-phishing-url-detection

ai api bidirectional-lstm deep-learning flask keras neuralnetwork tensorflow

Last synced: about 1 month ago
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AI: Deep Learning for Phishing URL Detection

• Host: GitHub
• URL: https://github.com/zpettry/ai-deep-learning-for-phishing-url-detection
• Owner: zpettry
• License: mit
• Created: 2018-12-02T23:09:13.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2022-12-08T01:19:41.000Z (about 2 years ago)
• Last Synced: 2023-03-03T14:00:52.420Z (almost 2 years ago)
• Topics: ai, api, bidirectional-lstm, deep-learning, flask, keras, neuralnetwork, tensorflow
• Language: Python
• Size: 1.81 MB
• Stars: 41
• Watchers: 1
• Forks: 12
• Open Issues: 9
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
AI: Deep Learning for Phishing URL Detection

=======================================

Model Performance

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![ROC/AUC Curve](http://www.zpettry.com/assets/roccurvezoomedin.JPG)

![Confusion Matrix](https://www.zpettry.com/assets/confusionmatrix_normalized.JPG)

![F1 Score](https://zpettry.com/assets/f1score.JPG)

Requirements

------------

This code was created with Python 3.6.7. Other versions of Python 3 might also work.  You can have multiple Python

versions (2.x and 3.x) installed on the same system without problems.

Make sure to install all requirements:

    $ pip install -r requirements.txt

NOTICE : Because of Github size limits, please download the model from here: https://www.zpettry.com/bi-lstmchar256256128.h5

Quick start

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Ensure the model has been downloaded from the above link.

Open a separate tab or window and run:

    $ python3 flaskrestapi.py

Now go back to the original tab or window and run:

    $ python3 request.py -u https://www.google.com/about

    Output:

    $ [{'malicious percentage': 2.552182786166668, 'result': 'URL is probably NOT malicious.', 'url': 'https://www.google.com/about'}]

Web site and documentation

--------------------------

Blog and additional information about this project is available at the web site:

  https://www.zpettry.com/

License

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This code is licensed under the terms of the MIT License (see the file

LICENSE).