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Computational Red Teaming: Risk Analytics of Big-Data-to-Decisions Intelligent Systems
Kategorie	Beschreibung
036a	XA-DE
037b	eng
087q	978-3-319-08280-6
100	Abbass, Hussein A.
331	Computational Red Teaming
335	Risk Analytics of Big-Data-to-Decisions Intelligent Systems
410	Cham
412	Springer
425	2015
425a	2015
433	Online-Ressource (XXIII, 218 p. 61 illus., 15 illus. in color, online resource)
451b	SpringerLink. Bücher
527	Druckausg.ISBN: 978-331-90828-0-6
540a	ISBN 978-3-319-08281-3
700	\|COM004000
700	\|UYQ
700	\|TEC009000
700b	\|006.3
700c	\|Q342
750	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
902s	209676493 Ingenieurwissenschaften
902s	209130482 Telekommunikation
902s	216543657 Big Data
012	417084129
081	Abbass, Hussein A.: Computational Red Teaming
100	Springer E-Book
125a	Elektronischer Volltext - Campuslizenz
655e	$uhttp://dx.doi.org/10.1007/978-3-319-08281-3