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Simulation framework for practical cyber security training in the public service

Deák Veronika

Security and Defence Quarterly

2021

Vol. 33, No. 1

87--104

The public service sector is a key target of cyberattacks. In order to prevent and effectively tackle such attacks, organisations should continuously develop their defence capabilities. As part of developing such capabilities, public service cybersecurity training is required to teach students about cyberattacks. The present study uses quantitative research techniques including (i) how to identify key requirements for the practical aspects of public service cybersecurity training and (ii) sampling to utilise international best practices from cybersecurity education and conceptual architectures from existing public service organisations. A schematic structure with a two-level practical training course is proposed. On the first level, the students learn about the defence mechanisms of their own info-communication devices and try to prevent attacks in a simulated environment. On the second level, the students apply protection strategies against cyberattacks in organisational infrastructure. Finally, a technical framework is defined to simulate cyberattacks against (a) personal devices and (b) a fictional organisational infrastructure. The specification of a public service cybersecurity training programme should not only focus on theoretical education but also provide practical knowledge to students. By simulating specific attacks, theoretical and practical knowledge can be combined. As a result, students will be able to recognise threats and potential risks from cyberspace.

The principal-agent problem in supply chain management – the simulation based framework

Siuta Kinga, Kaszyński Daniel

Control and Cybernetics

2021

Vol. 50, No. 1

195--221

This research deals with a phenomenon well-known in socio-economic studies and referred to as the Agency Theory: the principal-agent problem. The agent is designated to act on behalf of the company owner, i.e., the principal, in the domain of supply chain management in the face of a supplier’s default uncertainty. Each of the players is gain-oriented, but their objective functions and the degree of risk-bearing may significantly differ, leading to an agent’s decisions not being optimal in terms of the principal’s outcome. This article proposes a multi-period supply chain simulation model that can be used to perform a supply chain optimization and comparison between the agent and the principal. The proposed framework allows for differentiating the model parametrization depending on the industry, in particular the consequences of the inability to deliver the end product, costs of keeping safety stocks, or the uncertainty regarding the suppliers’ delivery failure. As players’ objective functions, we consider expected profit-based indicators and measures taking the inter-period variance into account. We find that the agent’s actions may diverge from the principal’s optimum if the agent’s incentive system is not selected correctly. We also propose a solution that unifies the goals of the players. The recent COVID-19 pandemic amplifies the importance of such research. Many companies had to limit production capacities due to global lockdowns and, per the JIT production strategy, the prior safety stock levels were low.