Subject: Computer and information sciences
Year: 2025
Type: Article
Type: PeerReviewed
Title: A Generic Taxonomy for Steganography Methods
Author: Wendzel, Steffen
Author: Caviglione, Luca
Author: Mazurczyk, Wojciech
Author: Mileva, Aleksandra
Author: Dittmann, Jana
Author: Krätzer, Christian
Author: Lamshöft, Kevin
Author: Vielhauer, Claus
Author: Hartmann, Laura
Author: Keller, Jörg
Author: Neubert, Tom
Author: Zillien, Sebastian
Abstract: A unified understanding of terms is essential for every scientific discipline: steganography is no exception. Being divided into several domains (e.g., network and text steganography), it is crucial to provide a unified terminology as well as a taxonomy that is not limited to few applications or areas. A prime attempt towards a unified understanding of terms was conducted in 2015 with the introduction of a pattern-based taxonomy for network steganography. In 2021, the first work towards a pattern-based taxonomy for all domains of steganography was proposed. However, this initial attempt still faced several shortcomings, e.g., remaining inconsistencies and a lack of patterns for several steganography domains. As the consortium who published the previous studies on steganography patterns, we present the first comprehensive pattern-based taxonomy tailored to fit all known domains of steganography, including smaller and emerging areas, such as filesystem, IoT/CPS, and AI/ML steganography. To make our contribution more effective and promote the use of the taxonomy to advance research, we also provide a unified description method joint with a thorough tutorial on its utilization.
Publisher: ACM
Relation: https://eprints.ugd.edu.mk/35943/
Identifier: oai:eprints.ugd.edu.mk:35943
Identifier: Wendzel, Steffen and Caviglione, Luca and Mazurczyk, Wojciech and Mileva, Aleksandra and Dittmann, Jana and Krätzer, Christian and Lamshöft, Kevin and Vielhauer, Claus and Hartmann, Laura and Keller, Jörg and Neubert, Tom and Zillien, Sebastian (2025) A Generic Taxonomy for Steganography Methods. ACM Computing Surveys, 57 (9). pp. 1-37. ISSN 0360-0300
Identifier: https://doi.org/10.1145/372916
