From Blind to Quantitative Steganalysis

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F12%3A00200175" target="_blank" >RIV/68407700:21230/12:00200175 - isvavai.cz</a>

Výsledek na webu

<a href="http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6081932&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6081932" target="_blank" >http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6081932&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6081932</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TIFS.2011.2175918" target="_blank" >10.1109/TIFS.2011.2175918</a>

Jazyk výsledku

angličtina

Název v původním jazyce

From Blind to Quantitative Steganalysis

Popis výsledku v původním jazyce

A quantitative steganalyzer is an estimator of the number of embedding changes introduced by a specific embedding operation. Since for most algorithms the number of embedding changes correlates with the message length, quantitative steganalyzers are important forensic tools. In this paper, a general method for constructing quantitative steganalyzers from features used in blind detectors is proposed. The core of the method is a support vector regression, which is used to learn the mapping between a feature vector extracted from the investigated object and the embedding change rate. To demonstrate the generality of the proposed approach, quantitative steganalyzers are constructed for a variety of steganographic algorithms in both JPEG transform and spatial domains. The estimation accuracy is investigated in detail and compares favorably with state-of-the-art quantitative steganalyzers.

Název v anglickém jazyce

From Blind to Quantitative Steganalysis

Popis výsledku anglicky

A quantitative steganalyzer is an estimator of the number of embedding changes introduced by a specific embedding operation. Since for most algorithms the number of embedding changes correlates with the message length, quantitative steganalyzers are important forensic tools. In this paper, a general method for constructing quantitative steganalyzers from features used in blind detectors is proposed. The core of the method is a support vector regression, which is used to learn the mapping between a feature vector extracted from the investigated object and the embedding change rate. To demonstrate the generality of the proposed approach, quantitative steganalyzers are constructed for a variety of steganographic algorithms in both JPEG transform and spatial domains. The estimation accuracy is investigated in detail and compares favorably with state-of-the-art quantitative steganalyzers.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

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Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název periodika

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY

ISSN

1556-6013

e-ISSN

—

Svazek periodika

7

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

10

Strana od-do

445-454

Kód UT WoS článku

000301506500009

EID výsledku v databázi Scopus

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