Application of Big Data for National Security

Application of Big Data for National Security

by Petra Saskia Bayerl, Andrew Staniforth, Richard Hill, Hamid R. Arabnia, Gregory B. Saathoff, Babak Akhgar
Released February 2015
Publisher(s): Butterworth-Heinemann
ISBN: 9780128019733

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Book description

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

Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. List of Contributors
  6. About the Editors
  7. Foreword by Lord Carlile of Berriew
  8. Preface by Edwin Meese III
  9. Acknowledgments
  10. Section 1. Introduction to Big Data
    1. Chapter 1. An Introduction to Big Data
      1. What Is Big Data?
      2. How Different Is Big Data?
      3. More on Big Data: Types and Sources
      4. The Five V’s of Big Data
      5. Big Data in the Big World
      6. Analytical Capabilities of Big Data
      7. Streaming Analytics
      8. An Overview of Big Data Solutions
      9. Conclusions
    2. Chapter 2. Drilling into the Big Data Gold Mine: Data Fusion and High-Performance Analytics for Intelligence Professionals
      1. Introduction
      2. The Age of Big Data and High-Performance Analytics
      3. Technology Challenges
      4. Examples
      5. Conclusion
  11. Section 2. Core Concepts and Application Scenarios
    1. Chapter 3. Harnessing the Power of Big Data to Counter International Terrorism
      1. Introduction
      2. A New Terror
      3. Changing Threat Landscape
      4. Embracing Big Data
      5. Conclusion
    2. Chapter 4. Big Data and Law Enforcement: Advances, Implications, and Lessons from an Active Shooter Case Study
      1. The Intersection of Big Data and Law Enforcement
      2. Case Example and Workshop Overview
      3. Situational Awareness
      4. Twitter as a Social Media Source of Big Data
      5. Social Media Data Analyzed for the Workshop
      6. Tools and Capabilities Prototypes during the Workshop
      7. Law Enforcement Feedback for the Sessions
      8. Discussion
    3. Chapter 5. Interpretation and Insider Threat: Rereading the Anthrax Mailings of 2001 Through a “Big Data” Lens
      1. Introduction
      2. Importance of the Case
      3. The Advancement of Big Data Analytics After 2001
      4. Relevant Evidence
      5. Potential for Stylometric and Sentiment Analysis
      6. Potential for Further Pattern Analysis and Visualization
      7. Final Words: Interpretation and Insider Threat
    4. Chapter 6. Critical Infrastructure Protection by Harnessing Big Data
      1. Introduction
      2. Understanding the Strategic Landscape into which Big Data Must Be Applied
      3. What Is Meant by an Overarching Architecture?
      4. Underpinning the SCR
      5. Strategic Community Architecture Framework
      6. Conclusions
    5. Chapter 7. Military and Big Data Revolution
      1. Risk of Collapse
      2. Into the Big Data Arena
      3. Simple to Complex Use Cases
      4. Canonic Use Cases
      5. More on the Digital Version of the Real World (See the World as Events)
      6. Real-Time Big Data Systems
      7. Implementing the Real-Time Big Data System
      8. Insight Into Deep Data Analytics Tools and Real-Time Big Data Systems
      9. Very Short Loop and Battlefield Big Data Datacenters
      10. Conclusions
    6. Chapter 8. Cybercrime: Attack Motivations and Implications for Big Data and National Security
      1. Introduction
      2. Defining Cybercrime and Cyberterrorism
      3. Attack Classification and Parameters
      4. Who Perpetrates These Attacks?
      5. Tools Used to Facilitate Attacks
      6. Motivations
      7. Attack Motivations Taxonomy
      8. Detecting Motivations in Open-Source Information
      9. Conclusion
  12. Section 3. Methods and Technological Solutions
    1. Chapter 9. Requirements and Challenges for Big Data Architectures
      1. What Are the Challenges Involved in Big Data Processing?
      2. Technological Underpinning
      3. Planning for a Big Data Platform
      4. Conclusions
    2. Chapter 10. Tools and Technologies for the Implementation of Big Data
      1. Introduction
      2. Techniques
      3. Analysis
      4. Computational Tools
      5. Implementation
      6. Project Initiation and Launch
      7. Data Sources and Analytics
      8. Analytics Philosophy: Analysis or Synthesis
      9. Governance and Compliance
    3. Chapter 11. Mining Social Media: Architecture, Tools, and Approaches to Detecting Criminal Activity
      1. Introduction
      2. Mining of Social Networks for Crime
      3. Text Mining
      4. Natural Language Methods
      5. General Architecture and Various Components of Text Mining
      6. Automatic Extraction of BNs from Text
      7. BNs and Crime Detection
      8. Conclusions
    4. Chapter 12. Making Sense of Unstructured Natural Language Information
      1. Introduction
      2. Big Data and Unstructured Data
      3. Aspects of Uncertainty in Sense Making
      4. Situation Awareness and Intelligence
      5. Processing Natural Language Data
      6. Structuring Natural Language Data
      7. Two Significant Weaknesses
      8. An Alternative Representation for Flexibility
      9. Conclusions
    5. Chapter 13. Literature Mining and Ontology Mapping Applied to Big Data
      1. Introduction
      2. Background
      3. ARIANA: Adaptive Robust Integrative Analysis for Finding Novel Associations
      4. Conceptual Framework of ARIANA
      5. Implementation of ARIANA for Biomedical Applications
      6. Case Studies
      7. Discussion
      8. Conclusions
    6. Chapter 14. Big Data Concerns in Autonomous AI Systems
      1. Introduction
      2. Artificially Intelligent System Memory Management
      3. Artificial Memory Processing and Encoding
      4. Constructivist Learning
      5. Practical Solutions for Secure Knowledge Development in Big Data Environments
      6. Conclusions
  13. Section 4. Legal and Social Challenges
    1. Chapter 15. The Legal Challenges of Big Data Application in Law Enforcement
      1. Introduction
      2. Legal Framework
      3. Conclusions
    2. Chapter 16. Big Data and the Italian Legal Framework: Opportunities for Police Forces
      1. Introduction
      2. European Legal Framework
      3. The Italian Legal Framework
      4. Opportunities and Constraints for Police Forces and Intelligence
    3. Chapter 17. Accounting for Cultural Influences in Big Data Analytics
      1. Introduction
      2. Considerations from Cross-Cultural Psychology for Big Data Analytics
      3. Cultural Dependence in the Supply and Demand Sides of Big Data Analytics
      4. (Mis)Matches among Producer, Production, Interpreter, and Interpretation Contexts
      5. Integrating Cultural Intelligence into Big Data Analytics: Some Recommendations
      6. Conclusions
    4. Chapter 18. Making Sense of the Noise: An ABC Approach to Big Data and Security
      1. How Humans Naturally Deal with Big Data
      2. The Three Stages of Data Processing Explained
      3. The Public Order Policing Model and the Common Operational Picture
      4. Applications to Big Data and Security
      5. Application to Big Data and National Security
      6. A Final Caveat from the FBI Bulletin
  14. Glossary
  15. Index

Product information

  • Title: Application of Big Data for National Security
  • Author(s): Petra Saskia Bayerl, Andrew Staniforth, Richard Hill, Hamid R. Arabnia, Gregory B. Saathoff, Babak Akhgar
  • Release date: February 2015
  • Publisher(s): Butterworth-Heinemann
  • ISBN: 9780128019733