Knowledge Discovery for Counterterrorism and Law Enforcement
Most of the research aimed at counterterrorism, fraud detection, or other forensic applications assumes that this is a specialized application domain for mainstream knowledge discovery. Unfortunately, knowledge discovery changes completely when the datasets being used have been manipulated in order to conceal some underlying activity. Knowledge Discovery for Counterterrorism and Law Enforcement operates from the premise that detection algorithms must be rethought to be effective in this domain, and presents a new approach based on cutting-edge analysis for use in adversarial settings.

Reveals How Criminals Conceal Information

This volume focuses on four main forms of knowledge discovery: prediction, clustering, relationship discovery, and textual analysis. For each of these application areas, the author discusses opportunities for concealment that are available to criminals and reveals some of the tactics that can aid in detecting them. He reviews what is known about the different technologies for each area and evaluates their effectiveness. The book also supplies a preview of technologies currently under development and describes how they will fit in to existing approaches to knowledge discovery.

Provides Proactive Formulas for Staying One Step Ahead of Adversaries

While all knowledge-discovery systems are susceptible to manipulation, designers and users of algorithmic systems who are armed with the knowledge of these subversive tactics are better able to create systems to avoid these vulnerabilities. This book delineates an effective process for integrating knowledge-discovery tools, provides a unique understanding of the limits of the technology, and contains a clear presentation of the upsides and pitfalls of data collection. It is a powerful weapon in the arsenal of anyone confronting the increasingly sophistic

1008860675
Knowledge Discovery for Counterterrorism and Law Enforcement
Most of the research aimed at counterterrorism, fraud detection, or other forensic applications assumes that this is a specialized application domain for mainstream knowledge discovery. Unfortunately, knowledge discovery changes completely when the datasets being used have been manipulated in order to conceal some underlying activity. Knowledge Discovery for Counterterrorism and Law Enforcement operates from the premise that detection algorithms must be rethought to be effective in this domain, and presents a new approach based on cutting-edge analysis for use in adversarial settings.

Reveals How Criminals Conceal Information

This volume focuses on four main forms of knowledge discovery: prediction, clustering, relationship discovery, and textual analysis. For each of these application areas, the author discusses opportunities for concealment that are available to criminals and reveals some of the tactics that can aid in detecting them. He reviews what is known about the different technologies for each area and evaluates their effectiveness. The book also supplies a preview of technologies currently under development and describes how they will fit in to existing approaches to knowledge discovery.

Provides Proactive Formulas for Staying One Step Ahead of Adversaries

While all knowledge-discovery systems are susceptible to manipulation, designers and users of algorithmic systems who are armed with the knowledge of these subversive tactics are better able to create systems to avoid these vulnerabilities. This book delineates an effective process for integrating knowledge-discovery tools, provides a unique understanding of the limits of the technology, and contains a clear presentation of the upsides and pitfalls of data collection. It is a powerful weapon in the arsenal of anyone confronting the increasingly sophistic

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Knowledge Discovery for Counterterrorism and Law Enforcement

Knowledge Discovery for Counterterrorism and Law Enforcement

by David Skillicorn
Knowledge Discovery for Counterterrorism and Law Enforcement

Knowledge Discovery for Counterterrorism and Law Enforcement

by David Skillicorn

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Overview

Most of the research aimed at counterterrorism, fraud detection, or other forensic applications assumes that this is a specialized application domain for mainstream knowledge discovery. Unfortunately, knowledge discovery changes completely when the datasets being used have been manipulated in order to conceal some underlying activity. Knowledge Discovery for Counterterrorism and Law Enforcement operates from the premise that detection algorithms must be rethought to be effective in this domain, and presents a new approach based on cutting-edge analysis for use in adversarial settings.

Reveals How Criminals Conceal Information

This volume focuses on four main forms of knowledge discovery: prediction, clustering, relationship discovery, and textual analysis. For each of these application areas, the author discusses opportunities for concealment that are available to criminals and reveals some of the tactics that can aid in detecting them. He reviews what is known about the different technologies for each area and evaluates their effectiveness. The book also supplies a preview of technologies currently under development and describes how they will fit in to existing approaches to knowledge discovery.

Provides Proactive Formulas for Staying One Step Ahead of Adversaries

While all knowledge-discovery systems are susceptible to manipulation, designers and users of algorithmic systems who are armed with the knowledge of these subversive tactics are better able to create systems to avoid these vulnerabilities. This book delineates an effective process for integrating knowledge-discovery tools, provides a unique understanding of the limits of the technology, and contains a clear presentation of the upsides and pitfalls of data collection. It is a powerful weapon in the arsenal of anyone confronting the increasingly sophistic


Product Details

ISBN-13: 9781420073997
Publisher: Taylor & Francis
Publication date: 11/13/2008
Series: Chapman & Hall/CRC Data Mining and Knowledge Discovery Series
Pages: 350
Product dimensions: 6.40(w) x 9.30(h) x 0.90(d)

About the Author

Skillicorn, David

Table of Contents

Introduction. Data. High-Level Principles. Looking for Risk - Prediction and Anomaly Detection. Looking for Similarity – Clustering. Looking Inside Groups - Relationship Discovery. Discovery from Public Textual Data. Discovery in Private Communication. Discovering Mental and Emotional State. The Bottom Line.

What People are Saying About This

From the Publisher

The writing is organized, clear, and free of technical jargon and mathematical notation. … In summary, this is a highly readable introduction to an interesting field. While it is certainly a valuable introductory resource for the technically adept, it is also appropriate for those with the desire to understand the applicability, potential,
and limitations of computer-assisted knowledge discovery techniques in counterterrorism and law enforcement.
Computing Reviews, September 2009

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