Node Criticality Assessment in Interdependent Networks via Decoupled Function Graphs

The traditional topology-based metrics for assessing node criticality may fall short in highly heterogeneous multilayer networks. This work introduces a novel modeling framework that incorporates both function and topology to effectively measure node criticality. The framework is applied to the State of Kansas’ transportation network as a practical example of an infrastructure network, identifying the most critical nodes under various operating load conditions. The findings reveal, among other insights, a significant rise in an adversary’s success rate when targeting the most critical nodes rather than a random set of nodes.