Detection of Steganography Inserted by OutGuess and Steghide by means of Neural Networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F09%3A63507970" target="_blank" >RIV/70883521:28140/09:63507970 - isvavai.cz</a>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Detection of Steganography Inserted by OutGuess and Steghide by means of Neural Networks

Popis výsledku v původním jazyce

The paper deals with detection of steganography content. Steganography is an additional method in cryptography which helps to hide coded messages inside pictures or videos. To hide a message is very important but also revealing such content is importantto avoid of usage by jailbirds. The revealing of steganography is not easy. This paper shows how neural networks are able to detect steganography content coded by a program OutGuess and Steghide using neural networks like taxonomist. Training sets were created from clear and coded pictures with different length of inserted message. Neural networks are methods which are very flexible in learning to different and difficult problems. Results in this paper show that used models had almost 100 % success in steganography detection of messages inserted by OutGuess and Steghide.

Název v anglickém jazyce

Detection of Steganography Inserted by OutGuess and Steghide by means of Neural Networks

Popis výsledku anglicky

The paper deals with detection of steganography content. Steganography is an additional method in cryptography which helps to hide coded messages inside pictures or videos. To hide a message is very important but also revealing such content is importantto avoid of usage by jailbirds. The revealing of steganography is not easy. This paper shows how neural networks are able to detect steganography content coded by a program OutGuess and Steghide using neural networks like taxonomist. Training sets were created from clear and coded pictures with different length of inserted message. Neural networks are methods which are very flexible in learning to different and difficult problems. Results in this paper show that used models had almost 100 % success in steganography detection of messages inserted by OutGuess and Steghide.

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

—

Projekt

<a href="/cs/project/GA102%2F09%2F1680" target="_blank" >GA102/09/1680: Evoluční návrh řídicích algoritmů</a><br>

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2009

Kód důvěrnosti údajů

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

Název statě ve sborníku

AMS2009 Asia Modelling Symposium 2009

ISBN

978-0-7695-3648-4

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

—

Název nakladatele

IEEE Operations Center

Místo vydání

Piscataway

Místo konání akce

Bandung

Datum konání akce

25. 5. 2009

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—