Analysis-on-GAN

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This is my project about Ransome Detection using GAN, the experiment was implemented by cuckoo.

Features:

• read report files from specific location (set in cuckoo) and extract features from them
• features engineering on choosing features with highest weights
• generate matrix based on the features(occurences of features)
• experiments with black attack for the GAN model
• experiments based on different parameters, number of hidden layers, number of nodes
• experiments based on ensemble classifiers
• experiments based on ensemble neural networks
• experiments on both ransomware dataset and generous malware

Pipelines：

- collect dataset:
    - please put the generated reports seperately under dataset folder
    - run the col_reports inside the processing (specify your own folder)

- generate raw features:
    - run the the feature_gen to generated seperate features

- get the total unique feature list:
    - run the feature_dict to get features list

- get the database based on feature occurrences
    - run the feature_fin to get dataset.csv

- classifier analysis (in classifiers):
   - analyse and filter the generated datasets and classifier algorithms

- model experiment:
    - test the models with filter features

For the ransomware and cuckoo configuration, please check the link cuckoo-download-instructions