A systematic review on cover selection methods for steganography: Trend analysis, novel classification and analysis of the elements

IF 13.3 1区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Muhammad Harith Noor Azam, Farida Ridzuan, M. Norazizi Sham Mohd Sayuti, A H Azni, Nur Hafiza Zakaria, Vidyasagar Potdar
{"title":"A systematic review on cover selection methods for steganography: Trend analysis, novel classification and analysis of the elements","authors":"Muhammad Harith Noor Azam, Farida Ridzuan, M. Norazizi Sham Mohd Sayuti, A H Azni, Nur Hafiza Zakaria, Vidyasagar Potdar","doi":"10.1016/j.cosrev.2025.100726","DOIUrl":null,"url":null,"abstract":"Cover selection is the process of selecting a suitable cover for steganography. Cover selection is crucial to maintain the steganographic characteristics performances and further avoid detection of hidden messages by eavesdroppers. Numerous existing reviews have focused mainly on the implementation and performance of steganography methods. Existing reviews have demonstrated inadequate depth of analysis and a lack of the number of articles reviewed. Thus, this article systematically reviews 34 cover selection methods for steganography in five databases including Web of Science, IEEE Xplore, ScienceDirect, Scopus, and Springer. The results include a trend analysis concerning existing cover selection algorithms for steganography. This article also establishes four novel classifications for cover selection methods. Recommendations on the implementation and design for cover selection method based on each class are provided. Analysis of the elements including cover types, datasets, searching methods, evaluation metrics for searching methods, cover selection attributes and its performance evaluations are also provided. An in-depth discussion on how cover types, searching method and evaluation metrics for searching method affects the steganography characteristics are also presented. This review offers valuable insights for researchers in developing new methods and enhance steganography systems for secure data communication.","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"55 1","pages":""},"PeriodicalIF":13.3000,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Science Review","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1016/j.cosrev.2025.100726","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

Cover selection is the process of selecting a suitable cover for steganography. Cover selection is crucial to maintain the steganographic characteristics performances and further avoid detection of hidden messages by eavesdroppers. Numerous existing reviews have focused mainly on the implementation and performance of steganography methods. Existing reviews have demonstrated inadequate depth of analysis and a lack of the number of articles reviewed. Thus, this article systematically reviews 34 cover selection methods for steganography in five databases including Web of Science, IEEE Xplore, ScienceDirect, Scopus, and Springer. The results include a trend analysis concerning existing cover selection algorithms for steganography. This article also establishes four novel classifications for cover selection methods. Recommendations on the implementation and design for cover selection method based on each class are provided. Analysis of the elements including cover types, datasets, searching methods, evaluation metrics for searching methods, cover selection attributes and its performance evaluations are also provided. An in-depth discussion on how cover types, searching method and evaluation metrics for searching method affects the steganography characteristics are also presented. This review offers valuable insights for researchers in developing new methods and enhance steganography systems for secure data communication.
隐写术封面选择方法综述:趋势分析、新分类和要素分析
封面选择是为隐写术选择合适的封面的过程。掩体选择对于保持隐写特征性能和进一步避免被窃听者发现隐藏信息至关重要。许多现有的评论主要集中在隐写方法的实现和性能上。现有的综述表明,分析的深度不足,而且综述的文章数量不足。因此,本文系统地综述了Web of Science、IEEE explore、ScienceDirect、Scopus和b施普林格等5个数据库中34种隐写术的封面选择方法。结果包括对隐写术现有封面选择算法的趋势分析。本文还建立了四种新的封面选择方法分类。提出了基于各类别的封面选择方法的实施和设计建议。分析了覆盖类型、数据集、搜索方法、搜索方法的评价指标、覆盖选择属性及其性能评价等要素。深入讨论了覆盖类型、搜索方法和搜索方法的评价指标对隐写特性的影响。这一综述为研究人员开发新的隐写方法和增强安全数据通信的隐写系统提供了有价值的见解。
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
Computer Science Review
Computer Science Review Computer Science-General Computer Science
CiteScore
32.70
自引率
0.00%
发文量
26
审稿时长
51 days
期刊介绍: Computer Science Review, a publication dedicated to research surveys and expository overviews of open problems in computer science, targets a broad audience within the field seeking comprehensive insights into the latest developments. The journal welcomes articles from various fields as long as their content impacts the advancement of computer science. In particular, articles that review the application of well-known Computer Science methods to other areas are in scope only if these articles advance the fundamental understanding of those methods.
×
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