BibSonomy ::  group :: css739 ::

(css739)  CV

Data mining is emerging as one of the key features of many homeland security initiatives. Often used as a means for detecting fraud, assessing risk, and product retailing, data mining involves the use of data analysis tools to discover previously unknown, valid patterns and relationships in large data sets. In the context of homeland security, data mining is often viewed as a potential means to identify terrorist activities, such as money transfers and communications, and to identify and track individual terrorists themselves, such as through travel and immigration records.

The ability of terrorist networks to conduct sophisticated and simultaneous attacks – the most recent one on March 11, 2004 in Madrid, Spain – suggests that there is a significant need for developing information technology tools for counter-terrorism analysis. These technologies could empower intelligence analysts to find information faster, share, and collaborate across agencies, "connect the dots" better, and conduct quicker and better analyses. One such technology, the Adaptive Safety Analysis and Monitoring (ASAM) system, is under development at the University of Connecticut. In this paper, the ASAM system is introduced and its capabilities are discussed. The vulnerabilities at the Athens 2004 Olympics are modeled and patterns of anomalous behavior are identified using a combination of featureaided multiple target tracking, hidden Markov models (HMMs), and Bayesian networks (BNs). Functionality of the ASAM system is illustrated by way of application to two hypothetical models of terrorist activities at the Athens 2004 Olympics.*

Abstract: Better ways are needed to understand how terrorist groups become more effective and dangerous. Learning is the link between what a group wants to do and its ability to actually do it; therefore, a better understanding of group learning might contribute to the design of better measures for combating terrorism. This study analyzes current understanding of group learning and the factors that influence it and outlines a framework that should be useful in present analytical efforts and for identifying areas requiring further study

Better ways are needed to understand how terrorist groups increase their effectiveness and become more dangerous. Learning is the link between what a group wants to do and its ability to actually do it; therefore, a better understanding of group learning might contribute to the design of better measures for combating terrorism. This study analyzes current understanding of group learning and the factors that influence it. It presents detailed case studies of learning in five terrorist organizations and develops a methodology for ascertaining what and why groups have learned, providing insights into their learning processes.