When sensor fusion operations are conducted in coalition environments, security of the data and infrastructure used for model fusion are very important. AI enabled sensor fusion infrastructure can be attacked on many fronts, including attacks on the data used for sensor information fusion and disrupting the communication between devices and the fusion nodes, in addition to the traditional security attacks. As the infrastructure for sensor fusion becomes more automated with multiple intelligent assistants for data collection, different types of attacks are possible. AI enabled approaches can be used to improve the security and resiliency of federated networks, and the data that is shared across coalition problems. In this paper, we discuss the challenges associated with security of coalition infrastructures, and approaches to improve the security using AI and machine learning techniques.