Discovering covert node in networked organization

This paper addresses a method to solve a node discovery problem in a complex network. Covert nodes which exist in a social network do not appear in the records which are observed on the communication or collaborative activities among the nodes. Discovering the covert nodes refers to identifying suspicious records in which the covert nodes would appear, or suspicious nodes which would be the neighbors of the covert nodes, if the covert nodes became overt. The mathematical model is developed for the maximal likelihood estimation of the network and for the identification of the suspicious records and nodes. Precision, recall, and F value characteristics are demonstrated with the test dataset generated from network models (real organization and mathematical model). The performance is close to the theoretical limit for any target covert nodes, network topologies, and network sizes if the ratio of the number of the observed data to the number of the possible communication patterns is high.