000 03628nam a22004695i 4500
001 978-3-319-08281-3
003 DE-He213
005 20200421111200.0
007 cr nn 008mamaa
008 141030s2015 gw | s |||| 0|eng d
020 _a9783319082813
_9978-3-319-08281-3
024 7 _a10.1007/978-3-319-08281-3
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aAbbass, Hussein A.
_eauthor.
245 1 0 _aComputational Red Teaming
_h[electronic resource] :
_bRisk Analytics of Big-Data-to-Decisions Intelligent Systems /
_cby Hussein A. Abbass.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aXXIII, 218 p. 61 illus., 15 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
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 _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.
650 0 _aEngineering.
650 0 _aData structures (Computer science).
650 0 _aComputational intelligence.
650 0 _aElectrical engineering.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aCommunications Engineering, Networks.
650 2 4 _aData Storage Representation.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319082806
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-08281-3
912 _aZDB-2-ENG
942 _cEBK
999 _c53751
_d53751