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Using Machine Learning for Malware Traffic Classification

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  • Python code to automate the execution of the clustering process.

** Step 1: Parse pcaps/bro logs into a JSON file

  • When parsing pcaps, run the pcap_processing/parse_bro_logs_v2.py script.
  • When parsing bro logs, run the pcap_processing/parse_logs.py script.

The output consist in the JSON file and a folder with the certificates.

** Step 2: Extract features

Run the clustering/prep/extract_features.py script, specifying the corresponding avclass and virustotal files, if any, and the folder with the certs. The TLS fingerprints can be located at clustering/data/tls_fprints/

The output is a TSV file with the feature vectors.

** Step 3: Run the clustering

When using the script clustering/run_clustering.py, a dataset_name must be specified. The script will look for two files into the data/groundtruth folder by default, the feature vectors (dataset_name.tsv) and the related avclass file (dataset_name.labels)

The output will be generated inside a folder with the same name as the dataset_name.

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