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README.markdown

About

dnsclass: open source, reference implementation of the DNS-Class algorithm in Python.

The classifier takes as input ARFF files generated with the Flowcalc program (using the dns and lpi plugins). dnsclass classifies given network traffic flows basing on their DNS context and outputs a classification report.

The classification process is divided into several steps, into script files named stepN_*, e.g. step6_predict.py. There are also scripts named cvN_* that support cross-validation.

For scientific works, please cite the following paper:

Foremski P., Callegari C., Pagano M., "DNS-Class: Immediate classification of IP flows using DNS"

Author: Paweł Foremski pjf@iitis.pl
Copyright (C) 2012-2013 IITiS PAN Gliwice
Licensed under GNU GPL v3

This software package uses libshorttext, which is included in the dnsclass repository, but may be licensed differently.

Classifier steps

The purpose of the steps:

  • step1_reformat.sh: reformat input ARFF files into the target text input format; skip all flows but those of selected protocols; some corrections may be required to match your ARFF files
  • step2_divide.sh: divide the dataset into training and testing (may be skipped)
  • step3_convert_train.py: convert the training dataset into the libsvm format (Vector Space Model (VSM))
  • step4_train.sh: train the model
  • step5_convert_test.py: as step 3, but for the testing dataset
  • step6_predict.py: classify the testing dataset
  • step7_analyze.py: show the confusion matrix and errors made in step 6

Project information

Project realized at The Institute of Theoretical and Applied Informatics of the Polish Academy of Sciences, under grant nr 2011/01/N/ST6/07202 of the Polish National Science Centre.

Project website: http://mutrics.iitis.pl/

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Reference implementation of the DNS-Class algorithm in Python

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