Optimization of Cross Diagonal Pixel Value Differencing and Modulus Function Steganography Using Edge Area Block Patterns

IF 1.2 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
Supriadi Rustad, Ignatius Moses Setiadi de Rosal, P. Andono, Abdul Syukur, Purwanto
{"title":"Optimization of Cross Diagonal Pixel Value Differencing and Modulus Function Steganography Using Edge Area Block Patterns","authors":"Supriadi Rustad, Ignatius Moses Setiadi de Rosal, P. Andono, Abdul Syukur, Purwanto","doi":"10.2478/cait-2022-0022","DOIUrl":null,"url":null,"abstract":"Abstract The existence of a trade-off between embedding capacity and imperceptibility is a challenge to improve the quality of steganographic images. This research proposes to cross diagonal embedding Pixel Value Differencing (PVD) and Modulus Function (MF) techniques using edge area patterns to improve embedding capacity and imperceptibility simultaneously. At the same time still, maintain a good quality of security. By implementing them into 14 public datasets, the proposed techniques are proven to increase both capacity and imperceptibility. The cross diagonal embedding PVD is responsible for increasing the embedding capacity reaching an average value of 3.18 bits per pixel (bpp), and at the same time, the implementation of edge area block patterns-based embedding is a solution of improving imperceptibility toward an average value of PSNR above 40 dB and that of SSIM above 0.98. Aside from its success in increasing the embedding capacity and the imperceptibility, the proposed techniques remain resistant to RS attacks.","PeriodicalId":45562,"journal":{"name":"Cybernetics and Information Technologies","volume":null,"pages":null},"PeriodicalIF":1.2000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cybernetics and Information Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/cait-2022-0022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 3

Abstract

Abstract The existence of a trade-off between embedding capacity and imperceptibility is a challenge to improve the quality of steganographic images. This research proposes to cross diagonal embedding Pixel Value Differencing (PVD) and Modulus Function (MF) techniques using edge area patterns to improve embedding capacity and imperceptibility simultaneously. At the same time still, maintain a good quality of security. By implementing them into 14 public datasets, the proposed techniques are proven to increase both capacity and imperceptibility. The cross diagonal embedding PVD is responsible for increasing the embedding capacity reaching an average value of 3.18 bits per pixel (bpp), and at the same time, the implementation of edge area block patterns-based embedding is a solution of improving imperceptibility toward an average value of PSNR above 40 dB and that of SSIM above 0.98. Aside from its success in increasing the embedding capacity and the imperceptibility, the proposed techniques remain resistant to RS attacks.
利用边缘区域块模式优化交叉对角线像素值差分和模函数隐写
摘要嵌入容量与隐写图像不可感知性之间的权衡是提高隐写图像质量的一个挑战。本研究提出利用边缘面积模式交叉对角嵌入像素值差分(PVD)和模函数(MF)技术,以同时提高嵌入容量和不可感知性。同时还保持了良好的安全质量。通过在14个公共数据集中实现它们,证明了所提出的技术提高了容量和不可感知性。交叉对角嵌入PVD可使嵌入容量提高到平均3.18 bits / pixel (bpp),同时,实现基于边缘区域块模式的嵌入是提高对PSNR平均值大于40 dB和SSIM平均值大于0.98的不可见性的解决方案。除了成功地提高了嵌入容量和不可感知性之外,所提出的技术仍然可以抵抗RS攻击。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Cybernetics and Information Technologies
Cybernetics and Information Technologies COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
3.20
自引率
25.00%
发文量
35
审稿时长
12 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信