Harvesting covert networks: A case study of the iMiner database

Data collection of covert networks is an inherently difficult task because of the very nature of these networks. Researchers find it difficult to locate and access data relating to the structure and function of such networks in order to study this extreme social phenomenon. In addition, information collected by intelligence agencies and government organisations is inaccessible to researchers. To counter the information scarcity, we designed and built a database of terrorist-related data and information by harvesting such data from publicly available authenticated websites. The database was incorporated in the iMiner prototype tool, which makes use of investigative data mining techniques to analyse data. This paper will present the developed framework along with the form and structure of the terrorist data in the database. Selected cases will be referenced to highlight the effectiveness of the iMiner tool and its applicability to real-life situations. © 2011 Inderscience Enterprises Ltd.