AuthorsJ. E. Hannay, A. Stolpe and M. M. Yamin
EditorsC. Stephanidis, M. Kurosu, J. Y. C. Chen, G. Fragomeni, N. Streitz, S. Konomi, H. Degen and S. Ntoa
TitleToward AI-Based Scenario Management for Cyber Range Training
AfilliationSoftware Engineering
Project(s)EDOS: Effective Digitalization of Public Sector
StatusPublished
Publication TypeBook Chapter
Year of Publication2021
Book TitleHCI International 2021 - Late Breaking Papers: Multimodality, eXtended Reality, and Artificial Intelligence
Series VolumeLNCS 13095
Pagination423–436
Date Published11/2021
PublisherSpringer International Publishing
Place PublishedCham
ISBN Number978-3-030-90963-5
Abstract

There is an immediate need for a greater number of highly skilled cybersecurity personnel to meet intensified cyber attacks. We propose a cyber range exercise management architecture that employs machine reasoning to structure the design, execution and analysis of cyber range training scenarios. The scenarios are then used in simulation-based training in an emulated IT infrastructure environment. The machine reasoning is obtained by combining four AI methods: attack-defence trees, formal argumentation theory, answer set programming and multiagent systems. We argue that this type of advanced functionality that supports exercise managers in their design and analysis of scenarios is strictly necessary to improve current exercise management systems and build the required cybersecurity expertise.