Cyberspace is changing the face of crime. For criminals it has become a place for rich collaboration and learning, not just within one country; and a place where new kinds of crimes can be carried out, and a vehicle for committing conventional crimes with unprecedented range, scale, and speed. Law enforcement faces a challenge in keeping up and dealing with this new environment. The news is not all bad – collecting and analyzing data about criminals and their activities can provide new levels of insight into what they are doing and how they are doing it. However, using data analytics requires a change of process and new skills that (so far) many law enforcement organizations have had difficulty leveraging. Cyberspace, Data Analytics, and Policing surveys the changes that cyberspace has brought to criminality and to policing with enough technical content to expose the issues and suggest ways in which law enforcement organizations can adapt.

Key Features:

Cyberspace is changing the face of crime. For criminals it has become a place for rich collaboration and learning, not just within one country; and a place where new kinds of crimes can be carried out, and a vehicle for committing conventional crimes with unprecedented range, scale, and speed. Law enforcement faces a challenge in keeping up and dealing with this new environment. The news is not all bad – collecting and analyzing data about criminals and their activities can provide new levels of insight into what they are doing and how they are doing it. However, using data analytics requires a change of process and new skills that (so far) many law enforcement organizations have had difficulty leveraging. Cyberspace, Data Analytics, and Policing surveys the changes that cyberspace has brought to criminality and to policing with enough technical content to expose the issues and suggest ways in which law enforcement organizations can adapt.

Key Features:

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.

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.

Cyberspace is changing the face of crime. For criminals it has become a place for rich collaboration and learning, not just within one country; and a place where new kinds of crimes can be carried out, and a vehicle for committing conventional crimes with unprecedented range, scale, and speed. Law enforcement faces a challenge in keeping up and dealing with this new environment. The news is not all bad – collecting and analyzing data about criminals and their activities can provide new levels of insight into what they are doing and how they are doing it. However, using data analytics requires a change of process and new skills that (so far) many law enforcement organizations have had difficulty leveraging. Cyberspace, Data Analytics, and Policing surveys the changes that cyberspace has brought to criminality and to policing with enough technical content to expose the issues and suggest ways in which law enforcement organizations can adapt.

Key Features:

Cyberspace is changing the face of crime. For criminals it has become a place for rich collaboration and learning, not just within one country; and a place where new kinds of crimes can be carried out, and a vehicle for committing conventional crimes with unprecedented range, scale, and speed. Law enforcement faces a challenge in keeping up and dealing with this new environment. The news is not all bad – collecting and analyzing data about criminals and their activities can provide new levels of insight into what they are doing and how they are doing it. However, using data analytics requires a change of process and new skills that (so far) many law enforcement organizations have had difficulty leveraging. Cyberspace, Data Analytics, and Policing surveys the changes that cyberspace has brought to criminality and to policing with enough technical content to expose the issues and suggest ways in which law enforcement organizations can adapt.

Key Features:

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.

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.