Implementation and extention of GHOST framework

During the creation of cyber exercises or large datasets for evaluation and validation, a large amount of background data needs to be generated for the obfuscation of the malicious traffic. One option is to use automation scripts, which will handle NPC machines for the generation of the background data. The GHOST framework developed by Carnegie Mellon University offers a powerful solution for the automation and management of a number of NPC machines.

Goal

The goal of this project is to continue the work we have done on extending the functionality of the GHOST framework by offering the possibility to manage and automate the launch and removal of multiple NPC machines. The ultimate goal will be to deploy the GHOST framework for the production of a dataset.

Expected outcome

updating and extending the source code on the GitLab server
1 blog post
1 poster
a project report documenting the advancement and the use of GHOST in dataset generation

Required skills

To start this project you should have some knowledge of:

Python programming script

Conditions

Applicant’s country of origin must be a member of EU or NATO

Tools and technologies

To achieve this project, you will use following tools and technologies:

Python programming language
use git to manage your source code
use GitLab to implement Continuous Implementation (CI)
framework for virtual network management (To be decided which)