Digital Forensics and Watermarking [electronic resource] : 17th International Workshop, IWDW 2018, Jeju Island, Korea, October 22-24, 2018, Proceedings /

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Material type: Text

TextSeries: Security and Cryptology ; 11378Publisher: Cham : Springer International Publishing : Imprint: Springer, 2019Edition: 1st ed. 2019Description: XI, 392 p. 167 illus., 101 illus. in color. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9783030113896

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Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:

005.824 23

LOC classification:

QA268

Online resources:

Click here to access online

Contents:

Deep Neural Networks for Digital Forensics -- Steganalysis and Identification -- Watermarking -- Reversible Data Hiding -- Steganographic Algorithms -- Identification and Security -- Deep Generative Models for Forgery and Its Detection.

In: Springer Nature eBookSummary: This book constitutes the refereed proceedings of the 17th International Workshop on Digital Forensics and Watermarking, IWDW 2018, held on Jeju Island, Korea, in October 2018. The 25 papers presented in this volume were carefully reviewed and selected from 43 submissions. The contributions are covering the following topics: deep neural networks for digital forensics; steganalysis and identification; watermarking; reversible data hiding; steganographic algorithms; identification and security; deep generative models for forgery and its detection. .

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This book constitutes the refereed proceedings of the 17th International Workshop on Digital Forensics and Watermarking, IWDW 2018, held on Jeju Island, Korea, in October 2018. The 25 papers presented in this volume were carefully reviewed and selected from 43 submissions. The contributions are covering the following topics: deep neural networks for digital forensics; steganalysis and identification; watermarking; reversible data hiding; steganographic algorithms; identification and security; deep generative models for forgery and its detection. .

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