Save 50% on book bundles
Immediately download your ebook while waiting for your print delivery. No promo code is needed.
Back to School Savings: Save up to 30% on print books and eBooks. No promo code needed.
Back to School Savings: Save up to 30%
Application of Big Data for National Security
A Practitioner’s Guide to Emerging Technologies
1st Edition - February 14, 2015
Authors: Babak Akhgar, Gregory B. Saathoff, Hamid R Arabnia, Richard Hill, Andrew Staniforth, Petra Saskia Bayerl
Paperback ISBN:
9 7 8 - 0 - 1 2 - 8 0 1 9 6 7 - 2
eBook ISBN:
9 7 8 - 0 - 1 2 - 8 0 1 9 7 3 - 3
Application of Big Data for National Security provides users with state-of-the-art concepts, methods, and technologies for Big Data analytics in the fight against terrorism and… Read more
Purchase Options
Application of Big Data for National Security provides users with state-of-the-art concepts, methods, and technologies for Big Data analytics in the fight against terrorism and crime, including a wide range of case studies and application scenarios. This book combines expertise from an international team of experts in law enforcement, national security, and law, as well as computer sciences, criminology, linguistics, and psychology, creating a unique cross-disciplinary collection of knowledge and insights into this increasingly global issue.
The strategic frameworks and critical factors presented in Application of Big Data for National Security consider technical, legal, ethical, and societal impacts, but also practical considerations of Big Data system design and deployment, illustrating how data and security concerns intersect. In identifying current and future technical and operational challenges it supports law enforcement and government agencies in their operational, tactical and strategic decisions when employing Big Data for national security
- Contextualizes the Big Data concept and how it relates to national security and crime detection and prevention
- Presents strategic approaches for the design, adoption, and deployment of Big Data technologies in preventing terrorism and reducing crime
- Includes a series of case studies and scenarios to demonstrate the application of Big Data in a national security context
- Indicates future directions for Big Data as an enabler of advanced crime prevention and detection
Strategic policy developers and advisors to government agencies, Senior leaders in Law Enforcement Agencies, Technology consultants, Security consultants, Database/information architects, Researchers, Postgraduate students enrolled in applied database/intelligent systems programs
- List of Contributors
- About the Editors
- Foreword by Lord Carlile of Berriew
- Preface by Edwin Meese III
- Acknowledgments
- Section 1. Introduction to Big Data
- Chapter 1. An Introduction to Big Data
- What Is Big Data?
- How Different Is Big Data?
- More on Big Data: Types and Sources
- The Five V’s of Big Data
- Big Data in the Big World
- Analytical Capabilities of Big Data
- Streaming Analytics
- An Overview of Big Data Solutions
- Conclusions
- Chapter 2. Drilling into the Big Data Gold Mine: Data Fusion and High-Performance Analytics for Intelligence Professionals
- Introduction
- The Age of Big Data and High-Performance Analytics
- Technology Challenges
- Examples
- Conclusion
- Chapter 1. An Introduction to Big Data
- Section 2. Core Concepts and Application Scenarios
- Chapter 3. Harnessing the Power of Big Data to Counter International Terrorism
- Introduction
- A New Terror
- Changing Threat Landscape
- Embracing Big Data
- Conclusion
- Chapter 4. Big Data and Law Enforcement: Advances, Implications, and Lessons from an Active Shooter Case Study
- The Intersection of Big Data and Law Enforcement
- Case Example and Workshop Overview
- Situational Awareness
- Twitter as a Social Media Source of Big Data
- Social Media Data Analyzed for the Workshop
- Tools and Capabilities Prototypes during the Workshop
- Law Enforcement Feedback for the Sessions
- Discussion
- Chapter 5. Interpretation and Insider Threat: Rereading the Anthrax Mailings of 2001 Through a “Big Data” Lens
- Introduction
- Importance of the Case
- The Advancement of Big Data Analytics After 2001
- Relevant Evidence
- Potential for Stylometric and Sentiment Analysis
- Potential for Further Pattern Analysis and Visualization
- Final Words: Interpretation and Insider Threat
- Chapter 6. Critical Infrastructure Protection by Harnessing Big Data
- Introduction
- Understanding the Strategic Landscape into which Big Data Must Be Applied
- What Is Meant by an Overarching Architecture?
- Underpinning the SCR
- Strategic Community Architecture Framework
- Conclusions
- Chapter 7. Military and Big Data Revolution
- Risk of Collapse
- Into the Big Data Arena
- Simple to Complex Use Cases
- Canonic Use Cases
- More on the Digital Version of the Real World (See the World as Events)
- Real-Time Big Data Systems
- Implementing the Real-Time Big Data System
- Insight Into Deep Data Analytics Tools and Real-Time Big Data Systems
- Very Short Loop and Battlefield Big Data Datacenters
- Conclusions
- Chapter 8. Cybercrime: Attack Motivations and Implications for Big Data and National Security
- Introduction
- Defining Cybercrime and Cyberterrorism
- Attack Classification and Parameters
- Who Perpetrates These Attacks?
- Tools Used to Facilitate Attacks
- Motivations
- Attack Motivations Taxonomy
- Detecting Motivations in Open-Source Information
- Conclusion
- Chapter 3. Harnessing the Power of Big Data to Counter International Terrorism
- Section 3. Methods and Technological Solutions
- Chapter 9. Requirements and Challenges for Big Data Architectures
- What Are the Challenges Involved in Big Data Processing?
- Technological Underpinning
- Planning for a Big Data Platform
- Conclusions
- Chapter 10. Tools and Technologies for the Implementation of Big Data
- Introduction
- Techniques
- Analysis
- Computational Tools
- Implementation
- Project Initiation and Launch
- Data Sources and Analytics
- Analytics Philosophy: Analysis or Synthesis
- Governance and Compliance
- Chapter 11. Mining Social Media: Architecture, Tools, and Approaches to Detecting Criminal Activity
- Introduction
- Mining of Social Networks for Crime
- Text Mining
- Natural Language Methods
- General Architecture and Various Components of Text Mining
- Automatic Extraction of BNs from Text
- BNs and Crime Detection
- Conclusions
- Chapter 12. Making Sense of Unstructured Natural Language Information
- Introduction
- Big Data and Unstructured Data
- Aspects of Uncertainty in Sense Making
- Situation Awareness and Intelligence
- Processing Natural Language Data
- Structuring Natural Language Data
- Two Significant Weaknesses
- An Alternative Representation for Flexibility
- Conclusions
- Chapter 13. Literature Mining and Ontology Mapping Applied to Big Data
- Introduction
- Background
- ARIANA: Adaptive Robust Integrative Analysis for Finding Novel Associations
- Conceptual Framework of ARIANA
- Implementation of ARIANA for Biomedical Applications
- Case Studies
- Discussion
- Conclusions
- Chapter 14. Big Data Concerns in Autonomous AI Systems
- Introduction
- Artificially Intelligent System Memory Management
- Artificial Memory Processing and Encoding
- Constructivist Learning
- Practical Solutions for Secure Knowledge Development in Big Data Environments
- Conclusions
- Chapter 9. Requirements and Challenges for Big Data Architectures
- Section 4. Legal and Social Challenges
- Chapter 15. The Legal Challenges of Big Data Application in Law Enforcement
- Introduction
- Legal Framework
- Conclusions
- Chapter 16. Big Data and the Italian Legal Framework: Opportunities for Police Forces
- Introduction
- European Legal Framework
- The Italian Legal Framework
- Opportunities and Constraints for Police Forces and Intelligence
- Chapter 17. Accounting for Cultural Influences in Big Data Analytics
- Introduction
- Considerations from Cross-Cultural Psychology for Big Data Analytics
- Cultural Dependence in the Supply and Demand Sides of Big Data Analytics
- (Mis)Matches among Producer, Production, Interpreter, and Interpretation Contexts
- Integrating Cultural Intelligence into Big Data Analytics: Some Recommendations
- Conclusions
- Chapter 18. Making Sense of the Noise: An ABC Approach to Big Data and Security
- How Humans Naturally Deal with Big Data
- The Three Stages of Data Processing Explained
- The Public Order Policing Model and the Common Operational Picture
- Applications to Big Data and Security
- Application to Big Data and National Security
- A Final Caveat from the FBI Bulletin
- Chapter 15. The Legal Challenges of Big Data Application in Law Enforcement
- Glossary
- Index
- No. of pages: 316
- Language: English
- Published: February 14, 2015
- Imprint: Butterworth-Heinemann
- Paperback ISBN: 9780128019672
- eBook ISBN: 9780128019733
BA
Babak Akhgar
Babak Akhgar is Professor of Informatics and Director of CENTRIC (Center of Excellence in Terrorism, Resilience, Intelligence and Organized Crime Research) at Sheffield Hallam University (UK) and Fellow of the British Computer Society. He has more than 100 refereed publications in international journals and conferences on information systems with specific focus on knowledge management (KM). He is member of editorial boards of several international journals and has acted as Chair and Program Committee Member for numerous international conferences. He has extensive and hands-on experience in the development, management and execution of KM projects and large international security initiatives (e.g., the application of social media in crisis management, intelligence-based combating of terrorism and organized crime, gun crime, cyber-crime and cyber terrorism and cross cultural ideology polarization). In addition to this he is the technical lead of two EU Security projects: “Courage” on Cyber-Crime and Cyber-Terrorism and “Athena” onthe Application of Social Media and Mobile Devices in Crisis Management. He has co-edited several books on Intelligence Management.. His recent books are titled “Strategic Intelligence Management (National Security Imperatives and Information and Communications Technologies)”, “Knowledge Driven Frameworks for Combating Terrorism and Organised Crime” and “Emerging Trends in ICT Security”. Prof Akhgar is member of the academic advisory board of SAS UK.
Affiliations and expertise
Professor of Informatics, Sheffield Hallam University, Sheffield, UKGS
Gregory B. Saathoff
Affiliations and expertise
Associate Professor of Research, University of Virginia, USAHA
Hamid R Arabnia
Hamid R. Arabnia is currently a Full Professor of Computer Science at University of Georgia where he has been since October 1987. His research interests include Parallel and distributed processing techniques and algorithms, interconnection networks, and applications in Computational Science and Computational Intelligence (in particular, in image processing, medical imaging, bioinformatics, and other computational intensive problems). Dr. Arabnia is Editor-in-Chief of The Journal of is Associate Editor of IEEE Transactions on Information Technology in Biomedicine . He has over 300 publications (journals, proceedings, editorship) in his area of research in addition he has edited two titles Emerging Trends in ICT Security (Elsevier 2013), and Advances in Computational Biology (Springer 2012).
Affiliations and expertise
Professor of Computer Science, University of Georgia, Athens, GA, USARH
Richard Hill
Affiliations and expertise
Department of Mathematics, University College London, UKAS
Andrew Staniforth
Andrew Staniforth, Detective Inspector and Advisory Board Member and Senior Research Fellow, Centre of Excellence in Terrorism, Resilience, Intelligence and Organised Crime Research (CENTRIC).
Affiliations and expertise
Detective Inspector and Senior Research Fellow, CENTRIC, Sheffield Hallam University, Sheffield, UKPB
Petra Saskia Bayerl
Affiliations and expertise
Visiting Fellow, CENTRIC, Netherlands