Some of the most important international security threats stem from terror groups, criminal enterprises, and other violent non-state actors (VNSAs). Because these groups are often structured as complex, dark networks, analysts have begun to use network science to study them. However, standard network tools were originally developed to examine companies, friendship groups, and other transparent networks. The inherently clandestine nature of dark networks dictates that conventional analytical tools do not always apply. Data on dark networks is incomplete, inaccurate, and often just difficult to find. Moreover, dark networks are often organized to undertake fundamentally different tasks than transparent networks, so resources and information may follow different paths through these two types of organizations. Given the distinctive characteristics of dark networks, unique tools and methods are needed to understand these structures. Illuminating Dark Networks explores the state of the art in methods to study and understand dark networks.

'Social network analysis is now a well-established paradigm within the social sciences and has been successfully applied to various types of relational data. However, until now, too little attention has been paid to how it should be applied to dark networks. Illuminating Dark Networks brings together leading academics, military researchers, and civilian analysts to provide the reader with the latest thinking on how to collect, analyze, and understand clandestine networks. Challenging traditional thinking and proposing new methods and ideas, this volume is timely, informative, and engaging.'

Martin Everett - Chair in Social Network Analysis, Mitchell Centre, University of Manchester

'Illuminating Dark Networks: The Study of Clandestine Groups and Organizations is a rare book title in that it conveys exactly what the book actually delivers. Drawing on work from some of the best researchers in this area, both from the policy world and academia, across fields as diverse as sociology, statistics, and computer science, this edited volume makes an important contribution to our understanding of dark networks and how to study them.'

Victor Asal - University at Albany, State University of New York