000			03590nam a22003735i 4500
999			_c103506 _d103506 _x1
001			103506
003			DE-He213
005			20240111050146.0
006			a||||fo|||| 00| 0
007			cr nn 008mamaa
008			141030s2015 gw | s |||| 0|eng d
020			_a9783319082813
024	7		_a10.1007/978-3-319-08281-3 _2doi
040			_bspa _dES-MaUEC
050		4	_aQ342 _b2015 EB
100	1		_aAbbass, Hussein A. _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _0http://id.loc.gov/authorities/names/n2001088714 _1http://viaf.org/viaf/85213019/ _936963
245	1	0	_aComputational Red Teaming _bRisk Analytics of Big-Data-to-Decisions Intelligent Systems _cby Hussein A. Abbass.
264		1	_aCham _bSpringer International Publishing _c2015
300			_a1 recurso en línea (XXIII, 218 páginas 61 ilustraciones, 15 ilustraciones a color.)
336			_2rdacontent _aTexto (visual) _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
490	0		_aEngineering (Springer-11647)
505	0		_aThe 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.
520	3		_aWritten 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.
988			_aEBSPRINGER_2018
650		7	_aInteligencia artificial _2embne _9413115
776	0	8	_iEdición impresa: _z9783319082806
776	0	8	_iEdición impresa: _z9783319082820
776	0	8	_iEdición impresa: _z9783319384412
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-08281-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2019 _dz _eIG _zSI