dga_detector

1. dga-dataset.txt: the raw data;
2. rnn_clf.py: the script which completes processing data, training model and evaluating performance;
3. test_api.py: the script which shows how to use the micro-service;
4. development_summary.txt: the report summarizing what have been explored and developed in this project;
5. api_instruction.txt: the instruction introducing where to find the docker image and how to use the micro-service;
6. models folder: serialized model objects;
7. micro-service folder: all scripts, files and objects needed for the micro-service;

The data was split into train, dev and test datasets, and RNN algorithm was applied to learn the pattern of character dependency.

The precision, recall and f1-score achieved on the test dataset are all nearly close to 100%, and AUC of the model is greater than 0.9999. Please find more details in development_summary.txt.