Evaluation method and optimization strategies of resilience for air & space defense system of systems based on kill network theory and improved self-information quantity

Abstract

Resilience of air & space defense system of systems (SoSs) is critical to national air defense security. However, the research on it is still scarce. In this study, the resilience of air & space defense SoSs is firstly defined and the kill network theory is established by combining super network and kill chain theory. Two cases of the SoSs are considered: (a) The kill chains are relatively homogenous; (b) The kill chains are relatively heterogenous. Meanwhile, two capability assessment methods, which are based on the number of kill chains and improved self-information quantity, respectively, are proposed. The improved self-information quantity modeled based on nodes and edges can achieve qualitative and quantitative assessment of the combat capability by using linguistic Pythagorean fuzzy sets. Then, a resilient evaluation index consisting of risk response, survivability, and quick recovery is proposed accordingly. Finally, network models for regional air defense and anti-missile SoSs are established respectively, and the resilience measurement results are verified and analyzed under different attack and recovery strategies, and the optimization strategies are also proposed. The proposed theory and method can meet different demands to evaluate combat capability and optimize resilience of various types of air & space defense and similar SoSs.