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This workshop shows how you can use an IP-based machine learning algorithm with Amazon SageMaker to augment and enrich findings from AWS Security services such as Amazon GuardDuty. You'll learn how to load the notebook in SageMaker, train the model, and score findings to determine abnormality of the activity.

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Using ML with SageMaker and GuardDuty to Identify Anomalous Traffic

(Formerly: Scalable, Automated Anomaly Detection with Amazon GuardDuty and SageMaker)

This workshop shows how you can use an IP-based machine learning algorithm with Amazon SageMaker to augment and enrich findings from AWS Security services such as Amazon GuardDuty. You'll learn how to load the notebook in SageMaker, train the model, and score findings to determine abnormality of the activity.

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Visit the site to get started: https://ml-threat-detection.awssecworkshops.com/

License

This library is licensed under the Apache 2.0 License.

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This workshop shows how you can use an IP-based machine learning algorithm with Amazon SageMaker to augment and enrich findings from AWS Security services such as Amazon GuardDuty. You'll learn how to load the notebook in SageMaker, train the model, and score findings to determine abnormality of the activity.

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  • Jupyter Notebook 69.0%
  • Python 26.6%
  • Shell 2.7%
  • Dockerfile 1.7%