Countering terrorism through information technology

Abstract

Developing the information-analysis tools for an effective multi-agency information-sharing effort.

A Survey of Operations Research Models and Applications in Homeland Security

“…Raghu et al (2005) discussed a collaborative decision-making framework for homeland security and a connectionist modeling approach that fuses disparate information from several sources. Popp et al (2004) approached threat analysis from an information technology (IT) perspective. They argued that improved IT can reduce the time needed for searching for data, harvesting data, preprocessing data, and turning the results into reports and briefs.…”

Text Clustering for Digital Forensics Analysis

“…Text mining [22][23][24][25][26], [40] provides an effective, automatic platform to support the analysis of digital textual evidences, which is a key issue for homeland security [10,11]. Clustering algorithms [27][28][29][30][31][32][33][34][35][36][37][38][39] can be applied to text mining to allow the automatic recognition of some sort of structure in the analyzed set of documents.…”

“…The dictionary collects all terms used to represent every document D, and can be assembled empirically by gathering the terms that occur at least once in the document collection D; by this representation one loses the original relative ordering of terms within each document. Different models [9,10] can be used to retrieve index terms and to generate the vector that represents a document D. However, the vector space model [14] is the most widely used method for document clustering. In [7] an augmented vector space model is proposed; this augmented space is characterized in the subsequent section.…”

Collaborative Tools for Counter-Terrorism Analysis

“…In order to collaborate efficiently and effectively, distributed teams within the intelligence community require a forum in which they can share ideas and solve complex problems, monitor their own effectiveness and dynamics as a team, systematically evaluate differing opinions, and generate alternative scenarios. Considering the massive amount of information and the difficulty in connecting the dots, a set of tools capable of automated evidence collection, evaluating alternative hypotheses, and supporting evidential reasoning would be invaluable [1]. In this paper, we focus on a set of collaborative tools for identifying, tracking, and mitigating terrorist activities.…”

“…Three major components of the collaborative environment are described and illustrated using an Indian Airlines (IA) hijacking example: (1) NEMESIS, which provides a forum for information exchange among multiple modeling or analysis tools, and model-based team collaboration; (2) ASAM, which is based on a novel combination of hidden Markov models (HMMs) to detect and provide soft evidence on the states of terrorist activities using partial and imperfect observations, and Bayesian network (BN) model that integrates the soft evidence from multiple HMMs and estimates global threats; and (3) ORA, which combines ideas from social network analysis, organizational theory, and computational sociology to model the information flow and diffusion within terrorist networks, evolution of terrorist networks, and other related concepts.…”