Click to open the HelpDesk interface
AECE - Front page banner

Menu:


FACTS & FIGURES

JCR Impact Factor: 0.699
JCR 5-Year IF: 0.674
Issues per year: 4
Current issue: Nov 2018
Next issue: Feb 2019
Avg review time: 79 days


PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


TRAFFIC STATS

2,163,656 unique visits
566,038 downloads
Since November 1, 2009



No robots online now


SJR SCImago RANK

SCImago Journal & Country Rank


SEARCH ENGINES

aece.ro - Google Pagerank




TEXT LINKS

Anycast DNS Hosting
MOST RECENT ISSUES

 Volume 18 (2018)
 
     »   Issue 4 / 2018
 
     »   Issue 3 / 2018
 
     »   Issue 2 / 2018
 
     »   Issue 1 / 2018
 
 
 Volume 17 (2017)
 
     »   Issue 4 / 2017
 
     »   Issue 3 / 2017
 
     »   Issue 2 / 2017
 
     »   Issue 1 / 2017
 
 
 Volume 16 (2016)
 
     »   Issue 4 / 2016
 
     »   Issue 3 / 2016
 
     »   Issue 2 / 2016
 
     »   Issue 1 / 2016
 
 
 Volume 15 (2015)
 
     »   Issue 4 / 2015
 
     »   Issue 3 / 2015
 
     »   Issue 2 / 2015
 
     »   Issue 1 / 2015
 
 
  View all issues  








LATEST NEWS

2018-Jun-27
Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

Read More »


    
 

  3/2018 - 3

Adaptive LSB Steganography Based on Chaos Theory and Random Distortion

TUTUNCU, K. See more information about TUTUNCU, K. on SCOPUS See more information about TUTUNCU, K. on IEEExplore See more information about TUTUNCU, K. on Web of Science, DEMIRCI, B. See more information about DEMIRCI, B. on SCOPUS See more information about DEMIRCI, B. on SCOPUS See more information about DEMIRCI, B. on Web of Science
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,291 KB) | Citation | Downloads: 260 | Views: 329

Author keywords
ciphers, chaos, data encapsulation, data security, digital images

References keywords
image(17), steganography(15), chaotic(11), hiding(10), steganographic(9), information(8), algorithm(8), communications(7), signal(5), security(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2018-08-31
Volume 18, Issue 3, Year 2018, On page(s): 15 - 22
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.03003
Web of Science Accession Number: 000442420900003
SCOPUS ID: 85052105181

Abstract
Quick view
Full text preview
Image steganography is a technique to hide secret information in an image without leaving any apparent evidence of image alteration. Hiding capacity, perceptual transparency, robustness, and resistance against attack must be considered as characteristics of the image steganography algorithms. In this study, Improved Chaos Based Bit Embedding has been proposed as a new steganography algorithm. It is based on two basic principles. One of them is determining the bits in which the secret data will be embedded by logistic map and the other one is embedding the secret data into only one of the three color channels that is chosen randomly. It distorts the other remaining channels so that it is harder to obtain the text within the image by an unwanted person. The proposed algorithm has been tested on 10 sample images along with the four basic steganography algorithms: Least Significant Bit Embedding, Pseudo Random Least Significant Bit Embedding, EzStego, and F5. It has been seen that generating unpredictable indexes by the chaotic random number generators, and embedding the secret data into only one of the three channels (distorting remaining channels) increased resistance against attacks. Perceptual transparencies and capacity ratio of the proposed algorithm are compatible with the other four algorithms.


References | Cited By

Cited-By ISI Web of Science

Web of Science® Times Cited: 0
View record in Web of Science® [View]
View Related Records® [View]

Updated today


Cited-By CrossRef

SCOPUS® Times Cited: 0
View record in SCOPUS®
[Free preview]

Updated today

Cited-By CrossRef

There are no citing papers in the CrossRef Cited-by Linking system.

Updated today

Disclaimer: All information displayed above was retrieved by using remote connections to respective databases. For the best user experience, we update all data by using background processes, and use caches in order to reduce the load on the servers we retrieve the information from. As we have no control on the availability of the database servers and sometimes the Internet connectivity may be affected, we do not guarantee the information is correct or complete. For the most accurate data, please always consult the database sites directly. Some external links require authentication or an institutional subscription.

Web of Science® is a registered trademark of Clarivate Analytics, Scopus® is a registered trademark of Elsevier B.V., other product names, company names, brand names, trademarks and logos are the property of their respective owners.


Copyright ©2001-2019
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.

Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.

Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.




Website loading speed and performance optimization powered by: