ML for false positive prediction

[fabriziosalmi]

1. Hourly Cron Job

• Use a cron job to run a Python script every hour.

  0 * * * * /usr/bin/python3 /path_to_your_script/your_script.py

2. Comparison with Whitelist

• Fetch the updated blacklist and compare it with the whitelist.

  blacklist = fetch_updated_blacklist()  # Define a function to fetch the updated blacklist
  whitelist = load_whitelist()  # Load the whitelist from a file or a database
  
  false_positives = set(blacklist).intersection(whitelist)  # Find overlaps between blacklist and whitelist

3. Machine Learning Model

• Use a pre-trained model to predict whether the identified overlaps are indeed false positives.

  model = load_pretrained_model()  # Load a pre-trained model
  
  for url in false_positives:
     is_false_positive = model.predict(url)  # Predict whether the URL is a false positive
     if is_false_positive:
         refine_blacklist(url)  # Remove the false positive from the blacklist

4. Refinement

• Refine the blacklist by removing the confirmed false positives.

  def refine_blacklist(url):
     blacklist.remove(url)  # Remove the URL from the blacklist
     save_updated_blacklist(blacklist)  # Save the updated blacklist to a file or a database

5. Alerting/Logging

• Log the results and send alerts if necessary.

  import logging
  
  logging.basicConfig(filename='blacklist_refinement.log', level=logging.INFO)
  
  if false_positives:
     logging.info(f"False positives identified and refined: {false_positives}")
     send_alert(false_positives)  # Define a function to send alerts, e.g., email

Additional Considerations:

• Model Training: Regularly retrain your model with new data to ensure it stays accurate.
• Performance Monitoring: Monitor the performance of your model and the accuracy of its predictions.
• User Feedback: Incorporate feedback from users to identify additional false positives/negatives and improve the model.

This is a high-level overview and pseudo-code.

[fabriziosalmi]

Doing a model from scratch for this purpose.

Check wiki documentation 🍻

[fabriziosalmi]

https://github.com/fabriziosalmi/blacklists/wiki/Machine-learning-%5Bhow-build-a-working-model-from-scratch%5D