Steganalysis by means of Artificial Neural Networks: Steganography detection in JPEG files by means of Artifical Neural Networks using Huffman coding

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F12%3A43868933" target="_blank" >RIV/70883521:28140/12:43868933 - isvavai.cz</a>

Result on the web

—

DOI - Digital Object Identifier

—

Result language

angličtina

Original language name

Steganalysis by means of Artificial Neural Networks: Steganography detection in JPEG files by means of Artifical Neural Networks using Huffman coding

Original language description

This book is focused on the revealing of hidden information present in multimedia files, mainly in pictures. This hidden information (messages) is coded in by means of steganography, which is an additional method of cryptography. Steganography provides better security for messages and the detection of such a message is not easy. The main goal of this research is a classification by means of artificial neural networks aimed at reducing false positive classification results to a minimum. To accomplish themain goal, a new model of image pre-processing was proposed. This pre-processing model is based on the Huffman coding, which is the main part of the lossless compression algorithm used in JPEG images. The Huffman coding can be easily transformed into the training sets for the artificial neural network, which is used as a classifier. The type of used artificial neural network was feed forward with supervision and Levenberg-Marquardt training algorithm. The results from performed simulati

Czech name

—

Czech description

—

Type

B - Specialist book

CEP classification

JD - Use of computers, robotics and its application

OECD FORD branch

—

Project

<a href="/en/project/ED2.1.00%2F03.0089" target="_blank" >ED2.1.00/03.0089: The Centre of Security, Information and Advanced Technologies (CEBIA-Tech)</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2012

Confidentiality

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

ISBN

978-3-659-30172-8

Number of pages

132

Publisher name

Lap Lambert Academic Publishing

Place of publication

Saarbrücken

UT code for WoS book

—