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.

When analysing how the information-technological innovation of a startup company is perceived to affect the market, we encountered challenges when using existing customer journey analysis frameworks. In particular, we identified a need to express critical events for technology adoption, a need to express universal access principles and a need to express journeys for multiple stakeholders in the same diagram; all in an easily readable manner. To do this, we extended an existing stripped-down customer journey framework with elements for the above aspects. We present this extended framework as a stakeholder journey framework. Based on the initial application of this framework on the startup company's innovation product, we conclude that the stakeholder journey framework aided in uncovering issues within technology adoption and universal access that would otherwise not have been addressed.