A study of graph simulation methodologies for synthetic Covert Social Network

Recent interest in Covert Social Network Analysis and problems in accessing realistic, complete social network dataset has catalyzed the development of numerous models to help artificially generate and understand these networks. Synthetic social network graph generators attempting to match properties of the realistic social networks. Generation of the artificial covert social network is still in the infancy state compared to artificial social network graph generation. In this paper we present a survey on artificial social network graph generation methodologies and artificial covert network graph generation techniques.