/IA-ID

Research into intrusion detection systems using artificial intelligence. Using on ISCX generated files

Primary LanguagePython

Intruvu

Data files are generated using the ISCX generator.

Installation

python -m virtualenv env
source env/bin/activate
pip install -r requirements.txt

Défi

Main file to launch for the challenge.

Execution

python defi.py

Arguments

  -h, --help            show this help message and exit
  -r                    Index files to ElasticSearch and exit the program.
                        Files must be indexed before working with classifiers.
  --index INDEX         Name of the ElasticSearch index to use.
                        default: "flow"
  --dir_train DIR_TRAIN
                        Directory to load the XML training file(s) from.
                        This directory contain the file(s) used for the training.
                        It shouldn't contain any file with unknown tag.
                        default: "./defi_train"
  --dir_test DIR_TEST   Directory to load the XML test file(s) from.
                        This directory contain the file(s) used for the test.
                        default: "./defi_test"
  --output OUTPUT       Name of the output file containing the results.
                        default: "output"

Use exemple

  1. Index files to ElasticSearch index "defi" from directories "train/" and "test/" containing training files and test files:

    python defi.py -r --index defi --dir_train train --dir_test test

  2. Train and classify test flows from index "defi" and print results to "results.txt" file:

    python defi.py --index defi --output results.txt

Main

Main file we used for the project. Its main use is to facilitate the comparison of different classifier.

Execution

python main.py

Arguments

  -h, --help            show this help message and exit
  -r                    Index files to ElasticSearch and exit the program.
                        Files must be indexed before working with classifiers.
  --index INDEX         Name of the ElasticSearch index to use.
                        default: "flow"
  --dir DIR             Directory to load the XML file(s) from. 
                        This directory contain the file(s) used for the classification.
                        default: "./ISCX_train"

Zipf

Display a Zipf diagram.

Execution

python zipf.py

Arguments

  -h, --help            show this help message and exit
  -r                    Index files to ElasticSearch and exit the program.
                        Files must be indexed before working with classifiers.
  --index INDEX         Name of the ElasticSearch index to use.
                        default: "flow"
  --dir DIR             Directory to load the XML file(s) from. 
                        This directory contain the file(s) used for the classification.
                        default: "./ISCX_train"