In this paper, we propose a new cybersecurity investment supply chain game theory model, assuming that the demands for the product are known and fixed and, hence, the conservation law of each demand market is fulfilled. The model is a generalized Nash equilibrium model with nonlinear budget constraints for which we define the variational equilibrium, which provides us with a variational inequality formulation. We construct an equivalent formulation, enabling the analysis of the influence of the conservation laws and the importance of the associated Lagrange multipliers. We find that the marginal expected transaction utility of each retailer depends on this Lagrange multiplier and its sign. Finally, numerical examples with reported equilibrium product flows, cybersecurity investment levels, and Lagrange multipliers, along with individual firm vulnerability and network vulnerability, illustrate the obtained results.
In this paper, we present a multi-tiered network-based optimization model describing the provision of services by network slices of 5G-Service providers (e.g. through Unmanned Aerial Vehicles (UAVs) organized as Flying Ad hoc Networks (FANET)), taking into account the security levels of each provider. The three levels of the network consist of the infrastructure layers, which contain resources needed to execute a service, the slices layer, where services are served for the services layer, which represents the upper layer of the network and consists of services or applications required by users or devices. The objective of the proposed model is to establish the optimal flows between network layers and the optimal security levels in order to maximize the providers’ profits, given by the difference between the revenues obtained by the sale of services and the rental of their resources and the costs. Numerical experiments are performed and solved with a new nature-inspired genetic algorithm adapted to the optimization 5G network problem.
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