Computational Red Teaming

Risk Analytics of Big-Data-to-Decisions Intelligent Systems

  • Hussein A. Abbass

Table of contents

  1. Front Matter
    Pages i-xxiii
  2. Hussein A. Abbass
    Pages 1-45
  3. Hussein A. Abbass
    Pages 47-104
  4. Hussein A. Abbass
    Pages 105-158
  5. Hussein A. Abbass
    Pages 159-185
  6. Hussein A. Abbass
    Pages 187-209
  7. Hussein A. Abbass
    Pages 211-216
  8. Back Matter
    Pages 217-218

About this book

Introduction

Written to bridge the information needs of management and computational scientists, this book presents the first comprehensive treatment of Computational Red Teaming (CRT).  The author describes an analytics environment that blends human reasoning and computational modeling to design risk-aware and evidence-based smart decision making systems. He presents the Shadow CRT Machine, which shadows the operations of an actual system to think with decision makers, challenge threats, and design remedies. This is the first book to generalize red teaming (RT) outside the military and security domains and it offers coverage of RT principles, practical and ethical guidelines.

The author utilizes Gilbert’s principles for introducing a science. Simplicity: where the book follows a special style to make it accessible to a wide range of  readers. Coherence:  where only necessary elements from experimentation, optimization, simulation, data mining, big data, cognitive information processing, and system thinking are blended together systematically to present CRT as the science of Risk Analytics and Challenge Analytics. Utility: where the author draws on a wide range of examples, ranging from job interviews to Cyber operations, before presenting three case studies from air traffic control technologies, human behavior, and complex socio-technical systems involving real-time mining and integration of human brain data in the decision making environment. 

 
• Presents first comprehensive treatment of Computational Red Teaming;

• Provides balanced coverage of the topic from the perspectives of risk thinking and computational modeling;

• Includes thorough coverage of the computational approach to the problem;

• Links risk analytics and challenge analytics with the right set of computational tools to assess risk in complex, “big-data” situations.

Keywords

Architecture Big Data Computational Intelligence Computational Red Teaming Data Mining Observe-Project-Counteract Agent

Authors and affiliations

  • Hussein A. Abbass
    • 1
  1. 1.School of Eng & Information TechnologyUniversity of New South Wales AustraliaCanberraAustralia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-08281-3
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-08280-6
  • Online ISBN 978-3-319-08281-3
  • About this book
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