Reprint

Data Hiding and Its Applications: Digital Watermarking and Steganography

Edited by
January 2022
234 pages
  • ISBN978-3-0365-2936-3 (Hardback)
  • ISBN978-3-0365-2937-0 (PDF)

This is a Reprint of the Special Issue Data Hiding and Its Applications: Digital Watermarking and Steganography that was published in

Biology & Life Sciences
Chemistry & Materials Science
Computer Science & Mathematics
Engineering
Environmental & Earth Sciences
Physical Sciences
Summary

Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others.

Format
  • Hardback
License and Copyright
© 2022 by the authors; CC BY-NC-ND license
Keywords
3D model; integrity protection; fragile watermarking; data hiding; genetic algorithm; Karhunen–Loève transform; screen-cam process; local square feature region; synchronization; DFT; robust watermarking; watermarking protocols; digital copyright protection; blockchain; block embedding; embedding capacity; embedding efficiency; optimal selection; parity assignment; steganograph; steganalysis; stegdetect; digital forensics; blockchain; digital watermarking; digital rights management; digital fingerprinting; cryptography; MIDI; velocity values; carrier file; stego file; capacity; steganalysis resilience; audibility; file-size change-rate; mean absolute error; peak signal-to-noise ratio; quantization level difference; AMBTC; reversible data hiding; high capacity; cryptographic hash function; hash chain; plausible deniability; steganography; covert channel; deep learning models; ownership; intellectual property; watermarking; security and privacy; private model; network covert channels; detection; stegomalware; traffic sanitization; normalization; propaganda detection; mixed-code identification; text analysis; machine learning; internet-based crimes; cyber terrorist networks; cyber-criminality; n/a