A Generic Taxonomy for Steganography Methods
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Date
2025-04-09
Authors
Wendzel, Steffen
Caviglione, Luca
Mazurczyk, Wojciech
Mileva, Aleksandra
Dittmann, Jana
Krätzer, Christian
Lamshöft, Kevin
Vielhauer, Claus
Hartmann, Laura
Keller, Jörg
Journal Title
Journal ISSN
Volume Title
Publication Type
Wissenschaftlicher Artikel
Published in
ACM Computing Surveys, 2025
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.
Description
Faculties
Fakultät für Ingenieurwissenschaften, Informatik und Psychologie
Institutions
Institut für Organisation und Management von Informationssystemen
Citation
DFG Project uulm
EU Project THU
Other projects THU
License
CC BY 4.0 International
Is version of
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Supplement to
Supplemented by
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Part of
DOI external
DOI external
10.1145/3729165
Institutions
Periodical
Degree Program
DFG Project THU
item.page.thu.projectEU
item.page.thu.projectOther
Series
Keywords
Steganographie, Mustererkennung, Cryptography, DDC 000 / Computer science, information & general works