In this paper, cyberattack detection and isolation is studied for a network of formation-flying unmanned aerial vehicles. As the unmanned aerial vehicles communicate to reach consensus on their states while making the formation, the communication network among the unmanned aerial vehicles makes them vulnerable to a potential attack from malicious adversaries. Two types of attacks pertinent to a network of unmanned aerial vehicles have been considered: a node attack on the unmanned aerial vehicles and a deception attack on the communication between the unmanned aerial vehicles. Unmanned aerial vehicle formation control involves using a consensus algorithm to maintain a prespecified formation. Two kinds of cyberattacks in the unmanned aerial vehicle network (node and communication path deception) are considered with their respective models in the formation setup. A bank of unknown input observer-based distributed fault detection schemes as well as with a rule based on residual generated using the bank of unknown input observers are proposed to detect the attacks and to identify the compromised unmanned aerial vehicle in the formation. Furthermore, an algorithm is developed to remove the faulty unmanned aerial vehicle from the network and to keep the compromised unmanned aerial vehicle isolated once an attack is detected, while maintaining the flight formation with a missing unmanned aerial vehicle node.