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Computational Red Teaming Risk Analytics of Big-Data-to-Decisions Intelligent Systems / by Hussein A. Abbass.

By: Abbass, Hussein A., autor.
Material type: materialTypeLabelE-bookSeries: (Engineering (Springer-11647)).Publisher: Cham : Springer International Publishing, 2015Description: 1 recurso en línea (XXIII, 218 páginas 61 ilustraciones, 15 ilustraciones a color.).ISBN: 9783319082813.Subject: Inteligencia artificialOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
The Art of Red Teaming -- Analytics of Risk and Challenge -- Big-Data-to-Decisions Red Teaming Systems -- Case Studies on Computational Red Teaming -- The Way Forward.
Abstract: 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.
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería Q342 .A233 2015 EB (Browse shelf(Opens below)) Acceso electrónico eBook.12112358
Total holds: 0

The Art of Red Teaming -- Analytics of Risk and Challenge -- Big-Data-to-Decisions Red Teaming Systems -- Case Studies on Computational Red Teaming -- The Way Forward.

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.

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