{"title":"A New Steganographic Algorithm for Hiding Messages in Music","authors":"M. Bajor, M. Niemiec","doi":"10.11610/isij.4718","DOIUrl":null,"url":null,"abstract":"Steganography in audio files usually revolves around well-known concepts and algorithms, least significant bit algorithm to name one. This paper proposes a new, alternative approach where steganographic information is connected with the medium even more – by using the medium itself as the information. The goal of this paper is to present a new aspect of steganography, which utilizes machine learning. This form of steganography may produce statistically indeterminable steganographic files which are immune to brute force attempts at trying to retrieve the hidden messages. Then the proposed solution is verified against statistical analysis and brute force attacks with promising results. A R T I C L E I N F O : RECEIVED: 04 JUNE 2020 REVISED: 24 AUG 2020 ONLINE: 22 SEP 2020 K E Y W O R D S : steganography, audio, MIDI format, machine learning Creative Commons BY-NC 4.0","PeriodicalId":159156,"journal":{"name":"Information & Security: An International Journal","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information & Security: An International Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11610/isij.4718","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Steganography in audio files usually revolves around well-known concepts and algorithms, least significant bit algorithm to name one. This paper proposes a new, alternative approach where steganographic information is connected with the medium even more – by using the medium itself as the information. The goal of this paper is to present a new aspect of steganography, which utilizes machine learning. This form of steganography may produce statistically indeterminable steganographic files which are immune to brute force attempts at trying to retrieve the hidden messages. Then the proposed solution is verified against statistical analysis and brute force attacks with promising results. A R T I C L E I N F O : RECEIVED: 04 JUNE 2020 REVISED: 24 AUG 2020 ONLINE: 22 SEP 2020 K E Y W O R D S : steganography, audio, MIDI format, machine learning Creative Commons BY-NC 4.0
音频文件中的隐写术通常围绕着众所周知的概念和算法,最低有效位算法就是其中之一。本文提出了一种新的替代方法,通过使用媒介本身作为信息,将隐写信息与媒介联系得更加紧密。本文的目标是介绍利用机器学习的隐写术的一个新方面。这种形式的隐写可能产生统计上无法确定的隐写文件,这些文件在试图检索隐藏信息时不受暴力破解的影响。通过统计分析和蛮力攻击验证了该方案的有效性。A R T I C L EI N F O:收稿日期:2020年6月4日修正值:2020年8月24日在线日期:2020年9月22日K E Y W O R D S:隐写,音频,MIDI格式,机器学习创作共用BY-NC 4.0