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An AMR adaptive steganography algorithm based on minimizing distortion.

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Title: An AMR adaptive steganography algorithm based on minimizing distortion.
Authors: Ren, Yanzhen1,2,3 renyz@whu.edu.cn, Wu, Hongxia1 13027150492@163.com, Wang, Lina1,2,3 lnawang@163.com
Source: Multimedia Tools & Applications. May2018, Vol. 77 Issue 10, p12095-12110. 16p.
Subjects: Cryptography software, Algorithm software, Statistics, Cost functions, Algorithms
Abstract: To improve the concealment and statistics security, the paper proposed an AMR (Adaptive Multi-Rate) FCB (Fixed CodeBook) Adaptive steganography scheme (AFA), which is based on the search principle of AMR FCB and the correlation of non-zero pulse positions. The key contribution of the scheme is the design of the cost function and the additive distortion function. The optimal probability of pulse and the pulse correlation in the same track were introduced to cost function to improve the statistics security of the proposed algorithm. The hit function b(n) which is used to search for optimal pulse position was added to additive distortion function to improve the concealment of the algorithm. The experiment results show that the proposed scheme has better hearing concealment and security performance to resist the detecting of the existing steganalysis algorithms than the other steganography schemes. [ABSTRACT FROM AUTHOR]
Copyright of Multimedia Tools & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: An AMR adaptive steganography algorithm based on minimizing distortion.
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  Data: <searchLink fieldCode="AR" term="%22Ren%2C+Yanzhen%22">Ren, Yanzhen</searchLink><relatesTo>1,2,3</relatesTo><i> renyz@whu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Wu%2C+Hongxia%22">Wu, Hongxia</searchLink><relatesTo>1</relatesTo><i> 13027150492@163.com</i><br /><searchLink fieldCode="AR" term="%22Wang%2C+Lina%22">Wang, Lina</searchLink><relatesTo>1,2,3</relatesTo><i> lnawang@163.com</i>
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  Data: <searchLink fieldCode="JN" term="%22Multimedia+Tools+%26+Applications%22">Multimedia Tools & Applications</searchLink>. May2018, Vol. 77 Issue 10, p12095-12110. 16p.
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  Data: <searchLink fieldCode="DE" term="%22Cryptography+software%22">Cryptography software</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithm+software%22">Algorithm software</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Cost+functions%22">Cost functions</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink>
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  Label: Abstract
  Group: Ab
  Data: To improve the concealment and statistics security, the paper proposed an AMR (Adaptive Multi-Rate) FCB (Fixed CodeBook) Adaptive steganography scheme (AFA), which is based on the search principle of AMR FCB and the correlation of non-zero pulse positions. The key contribution of the scheme is the design of the cost function and the additive distortion function. The optimal probability of pulse and the pulse correlation in the same track were introduced to cost function to improve the statistics security of the proposed algorithm. The hit function b(n) which is used to search for optimal pulse position was added to additive distortion function to improve the concealment of the algorithm. The experiment results show that the proposed scheme has better hearing concealment and security performance to resist the detecting of the existing steganalysis algorithms than the other steganography schemes. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Multimedia Tools & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: Statistics
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