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# 303COM_project_code | |
# Description | |
Code used during 303COM project to analyse unsupervised anomaly detection algorithms on Splunk and Elastic. | |
Three key files were used during development of this project. | |
All files pertaining to either Elastic (es) or Splunk (sp) begin with es/sp. | |
# Contents | |
* ```es_add_integers.py``` - Add all necessary string-to-integer conversions to raw OpTC file for use in Elastic X-pack outlier detection; also adds ground_truth field to help extract results of model | |
<br> | |
* ```sp_ml_statistics_calc.py``` - contains calculation class to determine performance of Splunk MLTK anomaly detection algorithms. Requires a CSV file in the format: ```_time, pid, hostname, outlier_prediction``` | |
<br> | |
* ```utils.py``` - contains necessary data to determine whether an event is a true positive and key dictionaries used for string-to-integer conversions. |