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Print ISSN: 1582-7445
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doi: 10.4316/AECE


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  4/2021 - 9

Quantum Steganography Using Two Hidden Thresholds

TUDORACHE, A.-G. See more information about TUDORACHE, A.-G. on SCOPUS See more information about TUDORACHE, A.-G. on IEEExplore See more information about TUDORACHE, A.-G. on Web of Science, MANTA, V. See more information about  MANTA, V. on SCOPUS See more information about  MANTA, V. on SCOPUS See more information about MANTA, V. on Web of Science, CARAIMAN, S. See more information about CARAIMAN, S. on SCOPUS See more information about CARAIMAN, S. on SCOPUS See more information about CARAIMAN, S. on Web of Science
 
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Download PDF pdficon (1,636 KB) | Citation | Downloads: 401 | Views: 355

Author keywords
data security, image communication, image processing, image representation, quantum computing

References keywords
quantum(45), process(20), steganography(19), image(15), images(8), zhou(7), novel(7), representation(5), protocol(5), digital(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2021-11-30
Volume 21, Issue 4, Year 2021, On page(s): 79 - 88
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2021.04009
Web of Science Accession Number: 000725107100009
SCOPUS ID: 85122237281

Abstract
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This paper describes a novel steganography algorithm that combines quantum computing with the least significant bit technique (LSB). Using the quantum properties, along with the Python programming language and the Qiskit framework for the circuit simulation, a sub-image can be hidden inside a usual image. For a gray image, this article presents how the LSB of each of the first 16 pixels on the edges can be used to hide two threshold values, that are then used to filter out the image and reveal the secret message. The speedup, compared to the classical version, is possible due to the quantum representation of an image (NEQR is used in this paper) and the efficiency of the novel multi-bit quantum comparators.


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References Weight

Web of Science® Citations for all references: 1,833 TCR
SCOPUS® Citations for all references: 2,690 TCR

Web of Science® Average Citations per reference: 51 ACR
SCOPUS® Average Citations per reference: 75 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2022-09-26 05:44 in 291 seconds.




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