Digital Media Steganography
Principles, Algorithms, and Advances

A comprehensive overview and application in image steganography and practical design

Mahmoud Hassaballah (Edited by)

9780128194386

Paperback, published 29 June 2020

386 pages, 120 illustrations (45 in full color)
23.4 x 19 x 2.5 cm, 0.79 kg

The common use of the Internet and cloud services in transmission of large amounts of data over open networks and insecure channels, exposes that private and secret data to serious situations. Ensuring the information transmission over the Internet is safe and secure has become crucial, consequently information security has become one of the most important issues of human communities because of increased data transmission over social networks. Digital Media Steganography: Principles, Algorithms, and Advances covers fundamental theories and algorithms for practical design, while providing a comprehensive overview of the most advanced methodologies and modern techniques in the field of steganography. The topics covered present a collection of high-quality research works written in a simple manner by world-renowned leaders in the field dealing with specific research problems. It presents the state-of-the-art as well as the most recent trends in digital media steganography.

1. Introduction to digital image steganography 2. A color image steganography method based on ADPVD and HOG techniques 3. An improved method for high hiding capacity based on LSB and PVD 4. An efficient image steganography method using multi-objective differential evolution 5. Image steganography using add-sub based QVD and side match 6. A high capacity invertible steganography method for Stereo image 7. An adaptive and clustering-based steganographic method: Osteg 8. A steganography method based on decomposition of the Catalan numbers 9. A steganography approach for hiding privacy in video surveillance systems 10. Reversible steganography techniques: A survey 11. Quantum Steganography 12. Digital media steganalysis 13. Unsupervised steganographer identification via clustering and outlier detection 14. Deep Learning in steganography and steganalysis

Subject Areas: Data encryption [URY], Forensic science [JKVF1]