Using meta-networks to identify key intervention points in nuclear WMD development

The ability to identify key intervention points in the nuclear WMD development process is vital for the development of effective intervention strategies against nuclear proliferation efforts. This paper describes research in progress to investigate nuclear weapons development as a meta-network of people, knowledge, resources, locations and tasks, and to design a software tool which will be capable of identifying the key intervention points of the process based upon the available information

Exploiting weaknesses: an approach to counter cartel strategy

The thesis, "Exploiting Weaknesses: An Approach to Counter Cartel Strategy," provided an in-depth case study analysis of Los Zetas transnational criminal network to gain an understanding on its weaknesses and vulnerabilities. The thesis utilized social movement theory to illuminate its mobilizing structure and key essential factors that make Los Zetas vulnerable to disruption. In addition, the study identified Los Zetas' financial support structure to expose its insidious methods. Finally, the thesis utilized social network analysis and geographical information systems to gain an understanding of its organizational networks, deduce possible safe havens, and key terrain of Los Zetas. Ultimately, the employment of the aforementioned theories revealed essential vulnerabilities, which form the essence of a practical disruption policy recommendation against Los Zetas.http://archive.org/details/exploitingweakne1094510682US Army (USA) author

A New Framework for Network Disruption

Traditional network disruption approaches focus on disconnecting or lengthening paths in the network. We present a new framework for network disruption that attempts to reroute flow through critical vertices via vertex deletion, under the assumption that this will render those vertices vulnerable to future attacks. We define the load on a critical vertex to be the number of paths in the network that must flow through the vertex. We present graph-theoretic and computational techniques to maximize this load, firstly by removing either a single vertex from the network, secondly by removing a subset of vertices.Comment: Submitted for peer review on September 13, 201

Detecting Covert Networks in Multilingual Groups: Evidence within a Virtual World

This paper introduces an approach for the examination and organization of unstructured text to identify relationships between networks of individuals. This approach uses discourse analysis to identify information providers and recipients and determines the structure of covert organizations irrespective of the language that facilitate conversations between members. Then, this method applies social network analytics to determine the arrangement of a covert organization without any a priori knowledge of the network structure. This approach is tested and validated using communication data collected in a virtual world setting. Our analysis indicates that the proposed framework successfully detected the covert structure of three information networks, and their cliques, within an online gaming community during a simulation of a large-scale event

Exploring Cyberterrorism, Topic Models and Social Networks of Jihadists Dark Web Forums: A Computational Social Science Approach

This three-article dissertation focuses on cyber-related topics on terrorist groups, specifically Jihadists’ use of technology, the application of natural language processing, and social networks in analyzing text data derived from terrorists\u27 Dark Web forums. The first article explores cybercrime and cyberterrorism. As technology progresses, it facilitates new forms of behavior, including tech-related crimes known as cybercrime and cyberterrorism. In this article, I provide an analysis of the problems of cybercrime and cyberterrorism within the field of criminology by reviewing existing literature focusing on (a) the issues in defining terrorism, cybercrime, and cyberterrorism, (b) ways that cybercriminals commit a crime in cyberspace, and (c) ways that cyberterrorists attack critical infrastructure, including computer systems, data, websites, and servers. The second article is a methodological study examining the application of natural language processing computational techniques, specifically latent Dirichlet allocation (LDA) topic models and topic network analysis of text data. I demonstrate the potential of topic models by inductively analyzing large-scale textual data of Jihadist groups and supporters from three Dark Web forums to uncover underlying topics. The Dark Web forums are dedicated to Islam and the Islamic world discussions. Some members of these forums sympathize with and support terrorist organizations. Results indicate that topic modeling can be applied to analyze text data automatically; the most prevalent topic in all forums was religion. Forum members also discussed terrorism and terrorist attacks, supporting the Mujahideen fighters. A few of the discussions were related to relationships and marriages, advice, seeking help, health, food, selling electronics, and identity cards. LDA topic modeling is significant for finding topics from larger corpora such as the Dark Web forums. Implications for counterterrorism include the use of topic modeling in real-time classification and removal of online terrorist content and the monitoring of religious forums, as terrorist groups use religion to justify their goals and recruit in such forums for supporters. The third article builds on the second article, exploring the network structures of terrorist groups on the Dark Web forums. The two Dark Web forums\u27 interaction networks were created, and network properties were measured using social network analysis. A member is considered connected and interacting with other forum members when they post in the same threads forming an interaction network. Results reveal that the network structure is decentralized, sparse, and divided based on topics (religion, terrorism, current events, and relationships) and the members\u27 interests in participating in the threads. As participation in forums is an active process, users tend to select platforms most compatible with their views, forming a subgroup or community. However, some members are essential and influential in the information and resources flow within the networks. The key members frequently posted about religion, terrorism, and relationships in multiple threads. Identifying key members is significant for counterterrorism, as mapping network structures and key users are essential for removing and destabilizing terrorist networks. Taken together, this dissertation applies a computational social science approach to the analysis of cyberterrorism and the use of Dark Web forums by jihadists