Robust steganographic method based on unconventional approach of neural networks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F18%3AA1901TZO" target="_blank" >RIV/61988987:17310/18:A1901TZO - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S1568494618301455" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1568494618301455</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.asoc.2018.03.023" target="_blank" >10.1016/j.asoc.2018.03.023</a>

Result language

angličtina

Original language name

Robust steganographic method based on unconventional approach of neural networks

Original language description

The article deals with the issue of using an apparatus of neural networks in the area of steganography. A new method called STEGONN was proposed. The proposed method is robust enough to an attack and the hidden message hard to be falsified. The core of our work lies in a design and implementation of a method for the use of neural networks as a native coder and decoder of a secret message (digital watermark) with an emphasis on the minimum necessary level of image data modification - covermedium. A covermedium is not perceived as a passive cover of a secret message, but we make active use of cover medium data, primarily its data markers (image markers) to insert a secret message. The advantage over other steganographic methods is the fact that the method implicitly offer the possibility to detect corrupted parts of the stegomedium and inform the user about possible manipulation with the image. The characteristics of the proposed method have been experimentally verified and compared with commercially available steganographic applications.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10200 - Computer and information sciences

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2018

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

APPL SOFT COMPUT

ISSN

1568-4946

e-ISSN

—

Volume of the periodical

67

Issue of the periodical within the volume

June

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

14

Pages from-to

505-518

UT code for WoS article

000431913000036

EID of the result in the Scopus database

2-s2.0-85044505511