LEADER 04373nam 2200757 450 001 9910137612703321 005 20230125234627.0 010 $a1-283-60392-6 010 $a9786613916372 010 $a1-118-43798-5 010 $a1-118-43796-9 010 $a1-118-43795-0 024 7 $a10.1002/9781118437957 035 $a(CKB)3190000000032947 035 $a(EBL)1022347 035 $a(SSID)ssj0000711543 035 $a(PQKBManifestationID)11416643 035 $a(PQKBTitleCode)TC0000711543 035 $a(PQKBWorkID)10722516 035 $a(PQKB)11028464 035 $a(DLC) 2012024649 035 $a(CaBNVSL)mat06331046 035 $a(IDAMS)0b0000648193ddab 035 $a(IEEE)6331046 035 $a(Au-PeEL)EBL1022347 035 $a(CaPaEBR)ebr10602086 035 $a(CaONFJC)MIL391637 035 $a(OCoLC)809555684 035 $a(CaSebORM)9781118437988 035 $a(MiAaPQ)EBC1022347 035 $a(PPN)244333815 035 $a(EXLCZ)993190000000032947 100 $a20151222d2012 uy 101 0 $aeng 135 $aurunu||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMachine learning in image steganalysis /$fHans Georg Schaathun 205 $a1st edition 210 1$aChichester, West Sussex, U.K. :$cJohn Wiley,$d2012. 210 2$a[Piscataqay, New Jersey] :$cIEEE Xplore,$d[2012] 215 $a1 online resource (394 p.) 225 1 $aWiley - IEEE 300 $aDescription based upon print version of record. 311 $a0-470-66305-7 320 $aIncludes bibliographical references and index. 327 $aFront Matter -- Overview. Introduction -- Steganography and Steganalysis -- Getting Started with a Classifier -- Features. Histogram Analysis -- Bit-Plane Analysis -- More Spatial Domain Features -- The Wavelets Domain -- Steganalysis in the JPEG Domain -- Calibration Techniques -- Classifiers. Simulation and Evaluation -- Support Vector Machines -- Other Classification Algorithms -- Feature Selection and Evaluation -- The Steganalysis Problem -- Future of the Field -- Bibliography -- Index. 330 $aSteganography is the art of communicating a secret message, hiding the very existence of a secret message. This is typically done by hiding the message within a non-sensitive document. Steganalysis is the art and science of detecting such hidden messages. The task in steganalysis is to take an object (communication) and classify it as either a steganogram or a clean document. Most recent solutions apply classification algorithms from machine learning and pattern recognition, which tackle problems too complex for analytical solution by teaching computers to learn from empirical data. Part 1of the book is an introduction to steganalysis as part of the wider trend of multimedia forensics, as well as a practical tutorial on machine learning in this context. Part 2 is a survey of a wide range of feature vectors proposed for steganalysis with performance tests and comparisons. Part 3 is an in-depth study of machine learning techniques and classifier algorithms, and presents a critical assessment of the experimental methodology and applications in steganalysis.Key features: . Serves as a tutorial on the topic of steganalysis with brief introductions to much of the basic theory provided, and also presents a survey of the latest research.. Develops and formalises the application of machine learning in steganalysis; with much of the understanding of machine learning to be gained from this book adaptable for future study of machine learning in other applications. . Contains Python programs and algorithms to allow the reader to modify and reproduce outcomes discussed in the book.. Includes companion software available from the author's website. 410 0$aWiley - IEEE 606 $aMachine learning 606 $aWavelets (Mathematics) 606 $aData encryption (Computer science) 615 0$aMachine learning. 615 0$aWavelets (Mathematics) 615 0$aData encryption (Computer science) 676 $a006.3/1 686 $aSCI067000$2bisacsh 700 $aSchaathun$b Hans Georg$0845658 801 0$bCaBNVSL 801 1$bCaBNVSL 801 2$bCaBNVSL 906 $aBOOK 912 $a9910137612703321 996 $aMachine learning in image steganalysis$91887878 997 $aUNINA LEADER 03187nam 22005775 450 001 9910874672703321 005 20240720122240.0 010 $a9783031491054$b(electronic bk.) 010 $z9783031491047 024 7 $a10.1007/978-3-031-49105-4 035 $a(MiAaPQ)EBC31538198 035 $a(Au-PeEL)EBL31538198 035 $a(CKB)33101354100041 035 $a(DE-He213)978-3-031-49105-4 035 $a(EXLCZ)9933101354100041 100 $a20240719d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aApplied Economic Research and Trends $e2023 International Conference on Applied Economics (ICOAE), Brno, Czech Republic, June 29-July 1, 2023 /$fedited by Nicholas Tsounis, Aspasia Vlachvei 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (1229 pages) 225 1 $aSpringer Proceedings in Business and Economics,$x2198-7254 311 08$aPrint version: Tsounis, Nicholas Applied Economic Research and Trends Cham : Springer International Publishing AG,c2024 9783031491047 327 $aNew methods and applications in Macroeconomics -- New methods and applications in Microeconomics -- New methods and applications in International Economics -- New methods and applications in Agricultural Economics -- New methods and applications in Financial Economics -- New methods and applications in Marketing and Management -- New methods and applications in Labour and Demographic Economics -- New methods and applications in Health Economics including analyses of effects of the COVID-19 pandemic on various economies -- New methods and applications in Education Economics. 330 $aThis volume presents new research and trends in applied economic research with special interest in advances in applied macroeconomics, microeconomics, financial economics, international economics, agricultural economics, health economics, marketing, and management. It features contributions presented at the 2023 International Conference on Applied Economics (ICOAE) held in Brno, Czech, Republic including country specific studies from 40 different countries. The contents of this volume is of interest to researchers, scholars, academics and policy makers within applied economics. 410 0$aSpringer Proceedings in Business and Economics,$x2198-7254 606 $aEconometrics 606 $aInternational economic relations 606 $aFinance 606 $aQuantitative Economics 606 $aInternational Economics 606 $aFinancial Economics 615 0$aEconometrics. 615 0$aInternational economic relations. 615 0$aFinance. 615 14$aQuantitative Economics. 615 24$aInternational Economics. 615 24$aFinancial Economics. 676 $a330.072 700 $aTsounis$b Nicholas$01379316 701 $aVlachvei$b Aspasia$01749477 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910874672703321 996 $aApplied Economic Research and Trends$94183702 997 $aUNINA