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Digital Forensics and Watermarking : 17th International Workshop, IWDW 2018, Jeju Island, Korea, October 22-24, 2018, Proceedings / edited by Chang D. Yoo, Yun-Qing Shi, Hyoung Joong Kim, Alessandro Piva, Gwangsu Kim.

SpringerLink Books Computer Science (2011-2024) Available online

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Format:
Book
Contributor:
Yoo, Chang D., Editor.
Shi, Yun-Qing., Editor.
Kim, Hyoung Joong., Editor.
Piva, Alessandro, Editor.
Kim, Gwangsu., Editor.
SpringerLink (Online service)
Series:
Computer Science (SpringerNature-11645)
LNCS sublibrary. Security and cryptology ; SL 4, 11378
Security and Cryptology ; 11378
Language:
English
Subjects (All):
Cryptography.
Data encryption (Computer science).
Data protection.
Computer crimes.
Computer vision.
Coding theory.
Information theory.
Artificial intelligence.
Cryptology.
Data and Information Security.
Computer Crime.
Computer Vision.
Coding and Information Theory.
Artificial Intelligence.
Local Subjects:
Cryptology.
Data and Information Security.
Computer Crime.
Computer Vision.
Coding and Information Theory.
Artificial Intelligence.
Physical Description:
1 online resource (XI, 392 pages) : 167 illustrations, 101 illustrations in color.
Edition:
1st ed. 2019.
Contained In:
Springer Nature eBook
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2019.
System Details:
text file PDF
Summary:
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. .
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.
Other Format:
Printed edition:
ISBN:
978-3-030-11389-6
9783030113896
Access Restriction:
Restricted for use by site license.

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