Data fusion provides a means for combining pieces of information from various sources and sensors. This chapter presents a data fusion methodology for interdependent critical infrastructures that leverages a distributed algorithm that allows the sharing of the possible causes of faults or threats affecting the infrastructures, thereby enhancing situational awareness. Depending on the degree of coupling, the algorithm modulates the information content provided by each infrastructure using a data fusion technique called evidence discounting. The methodology is applied to a case study involving a group of dependent critical infrastructures. Simulation results demonstrate that the methodology is resilient to temporary faults in the critical infrastructure communications layer.