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Cryptography
Article . 2022 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Cryptography
Article . 2022
Data sources: DOAJ
DBLP
Article . 2022
Data sources: DBLP
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Subliminal Channels in Visual Cryptography

Authors: Katarzyna Koptyra; Marek R. Ogiela;

Subliminal Channels in Visual Cryptography

Abstract

This paper describes three methods of creating a subliminal channel in visual cryptography that are defined for a (2,2) sharing scheme. They work by hiding additional covert information besides the original encrypted image. The first channel is revealed when the user folds the share along the specific axis. The second channel encodes subpixels on the basis of the encrypted message bits. It is designed to hide a wide range of data types. The third channel may be applied to a single share or multiple shares and is revealed when the proper parts of the shares are stacked. Fold and overlapping algorithms are adequate for printed shares, but the encryption method is only suitable for digital shares. The capacity of these methods ranges from half of the image size to the whole image size. The presented algorithms work on black-and-white images but are expandable to color visual cryptography. They may find applications in steganography and other data-hiding techniques. The created subliminal channels do not interfere with regular images that may still be revealed by stacking the shares. In short, this article introduces subliminal channels in visual cryptography, presents three algorithms for both binary and colorful images, shows examples of use with the results obtained, and discusses features of each method.

Keywords

Technology, visual cryptography, T, subliminal channel, steganography, information hiding

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
gold