LEADER 04366nam 22006375 450 001 9910299859703321 005 20200706113623.0 010 $a3-319-08281-7 024 7 $a10.1007/978-3-319-08281-3 035 $a(CKB)3710000000269613 035 $a(EBL)1965237 035 $a(SSID)ssj0001372463 035 $a(PQKBManifestationID)11785442 035 $a(PQKBTitleCode)TC0001372463 035 $a(PQKBWorkID)11303930 035 $a(PQKB)10829351 035 $a(DE-He213)978-3-319-08281-3 035 $a(MiAaPQ)EBC1965237 035 $a(PPN)182093069 035 $a(EXLCZ)993710000000269613 100 $a20141030d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aComputational Red Teaming $eRisk Analytics of Big-Data-to-Decisions Intelligent Systems /$fby Hussein A. Abbass 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (239 p.) 300 $aDescription based upon print version of record. 311 $a3-319-08280-9 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $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. 330 $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. 606 $aComputational intelligence 606 $aElectrical engineering 606 $aData structures (Computer science) 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aCommunications Engineering, Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/T24035 606 $aData Storage Representation$3https://scigraph.springernature.com/ontologies/product-market-codes/I15025 615 0$aComputational intelligence. 615 0$aElectrical engineering. 615 0$aData structures (Computer science). 615 14$aComputational Intelligence. 615 24$aCommunications Engineering, Networks. 615 24$aData Storage Representation. 676 $a004.5 676 $a006.3 676 $a620 676 $a621.382 700 $aAbbass$b Hussein A$4aut$4http://id.loc.gov/vocabulary/relators/aut$0720713 906 $aBOOK 912 $a9910299859703321 996 $aComputational Red Teaming$91412370 997 $aUNINA