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Detecting malicious URLs using an autoencoder neural network

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slrbl/malicious-urls-detection-with-autoencoder-neural-networks

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This repository contains the source code of Detecting malicious URLs using an autoencoder neural network.An article describing how it works is available athttps://www.linkedin.com/pulse/anomaly-detection-autoencoder-neural-network-applied-urls-daboubi/

Requirements

  • Python 3.9
  • x64 CPU
  • Tensorflow-compatible NVIDIA GPU

Install required libraries

pip3 install -r requirements.txt

Merge Inversion blocklist (Google_hostnames.txt) with url_data.csv

python merge_url_data.py

Generated new enriched data

python enrich_urls_data.py

Build and test a model

python train_and_test_urls_autoencoder.py

TODO

To put in place a REST API

Dataset sources

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