Disruption strategies for online child pornography networks

The advent of the Internet has allowed for the creation of online child pornography networks, in which websites link to one another and facilitate access to child pornographic materials. This project seeks to use social network analysis tools to identify effective disruption strategies against online child pornography networks. For this purpose, four networks of child exploitation material were extracted using a specially designed web-crawler. These networks were then submitted to three different attack strategies (hub, bridge, and fragmentation attacks), the effects of which were measured on three outcome measures (density, clustering, and reachability). It was found that, to reduce density and clustering, hub attacks were generally the most effective strategy. Conversely, to reduce reachability, fragmentation attacks were the most successful strategy. In addition, fragmentation attacks are valuable for extremely large attacks across all outcome measures (e.g., when over half of the network nodes are removed). Variables such as network size and type did not appear to influence the effectiveness of attack strategies. Implications for law enforcement practice and future research are examined.