Way Forward on Counter-Terrorism: Global Perspectives

Data Mining for Counter-Terrorism

Data mining is becoming a useful tool for detecting and preventing terrorism. This paper first discusses some technical challenges for data mining as applied for counterterrorism applications. Next it provides an overview of the various types of terrorist threats and describes how data mining techniques could provide solutions to counterterrorism. Finally some privacy concerns and potential sol...

Workshop on Data Mining for Counter Terrorism and Security

Data mining is playing an increasingly important role in sifting through large amount of data for homeland defense applications. However, we must pay attention to the privacy issues while mining the data. This has resulted in the development of several privacy-preserving data mining techniques. The random value distortion technique is one among them. It attempts to hide the sensitive data by ra...

A Neural Network for Counter-Terrorism

This article presents findings concerned with the use of neural networks in the identification of deceptive behaviour. A game designed by psychologists and criminologists was used for the generation of data used to test the appropriateness of different AI techniques in the quest for counter-terrorism. A feed forward back propagation network was developed and subsequent neural network experiment...

Graph Theory, Social Networks and Counter Terrorism

Modeling Values for Counter-Terrorism Analysis

Decisions are made to achieve objectives. A value model unambiguously represents objectives in a quantitative manner. Hence, a value model both guides thinking and provides a basis for analyzing alternatives to best meet the desired objectives. This paper proposes the development of value models to support counter-terrorism efforts. It summarizes the theory and procedures to develop value model...