Digital Media Steganography

Principles, Algorithms, and Advances
Erscheinungsjahr 2020
ISBN: 978-0-12-819438-6
Verlag: Elsevier Science

Buch, Englisch, 386 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 790 g

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.

Zielgruppe

Primary: Researchers, Scholars, Postgraduate Students, Students taking advanced course in related topics (e.g, Cryptography and data security). Secondary: PhD Studentsworldwide and Developers interested in steganography and information hiding, and connected research disciplines, Senior Undergraduate Students who take advanced topics in network security or advanced topics in data security courses

Autoren/Hrsg.

Hassaballah, Mahmoud

Fachgebiete

• Sozialwissenschaften Soziologie | Soziale Arbeit Spezielle Soziologie Kriminalsoziologie
• Sozialwissenschaften Medien- und Kommunikationswissenschaften Kommunikationswissenschaften Digitale Medien, Internet, Telekommunikation

Inhaltsverzeichnis

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

Über Autor(innen)

Hassaballah, Mahmoud
M. Hassaballa received his B.Sc. degree in mathematics in 1997 and his M.Sc. degree in computer science in 2003, both from South Valley University, Egypt, and his Doctor of Engineering (D. Eng.) in computer science from Ehime University, Japan in 2011. He is currently an associate professor of computer science at the Faculty of Computers and Information, South Valley University, Egypt. He served as a reviewer for several Journals. He has published 5 books and over 50 research papers in refereed international journals and conferences. His research interests include feature extraction, object detection/recognition, artificial intelligence, biometrics, image processing, computer vision, machine learning, and data hiding.