GitPlanet

Cheap and reliable Node.js hosting starts at $3/month, and $1/month static HTML hosting

Created with love in Canada, visit hostnodejs.com today

Feel like to post an Ad? Learn Details
All Projects → zpettry → AI-Deep-Learning-for-Phishing-URL-Detection

zpettry / AI-Deep-Learning-for-Phishing-URL-Detection

Licence: MIT license
AI: Deep Learning for Phishing URL Detection

Programming Languages

python
139335 projects - #7 most used programming language

Labels

apiflaskaideep-learningtensorflowkerasneuralnetworkbidirectional-lstm

Projects that are alternatives of or similar to AI-Deep-Learning-for-Phishing-URL-Detection

deepbgc
BGC Detection and Classification Using Deep Learning
Stars: ✭ 70 (+94.44%)
Mutual labels:  bidirectional-lstm
NeuralNetwork
A simple Neural Network in C#
Stars: ✭ 17 (-52.78%)
Mutual labels:  neuralnetwork
Nindamani-the-weed-removal-robot
Nindamani, the AI based mechanically weed removal robot
Stars: ✭ 73 (+102.78%)
Mutual labels:  neuralnetwork
Keras-LSTM-Trajectory-Prediction
A Keras multi-input multi-output LSTM-based RNN for object trajectory forecasting
Stars: ✭ 88 (+144.44%)
Mutual labels:  bidirectional-lstm
Plant-Disease-Identification-using-CNN
Plant Disease Identification Using Convulutional Neural Network
Stars: ✭ 89 (+147.22%)
Mutual labels:  neuralnetwork
Handwritten-Names-Recognition
The goal of this project is to solve the task of name transcription from handwriting images implementing a NN approach.
Stars: ✭ 54 (+50%)
Mutual labels:  neuralnetwork
Improved-Wasserstein-GAN-application-on-MRI-images
Improved Wasserstein GAN (WGAN-GP) application on medical (MRI) images
Stars: ✭ 23 (-36.11%)
Mutual labels:  neuralnetwork
WWW2020-grec
Future Data Helps Training: Modeling Future Contexts for Session-based Recommendation
Stars: ✭ 17 (-52.78%)
Mutual labels:  bidirectional-lstm
theano-recurrence
Recurrent Neural Networks (RNN, GRU, LSTM) and their Bidirectional versions (BiRNN, BiGRU, BiLSTM) for word & character level language modelling in Theano
Stars: ✭ 40 (+11.11%)
Mutual labels:  bidirectional-lstm

AI: Deep Learning for Phishing URL Detection

Model Performance

ROC/AUC Curve Confusion Matrix F1 Score

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

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

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

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].