基于分段STC的音频隐写算法

张雪垣; 王让定; 严迪群; 林昱臻

doi:10.11959/j.issn.1000-0801.2019071

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基于分段STC的音频隐写算法

研究与开发 | 更新时间：2024-06-05

- 基于分段STC的音频隐写算法
- An audio steganography algorithm based on segment-STC
- 电信科学 2019年35卷第7期页码：115-123
- 作者机构：
- 作者简介：
  
  [ "张雪垣（1994- ），男，宁波大学信息科学与工程学院硕士生，主要研究方向为多媒体通信、信息安全、信息隐写与隐写分析等。" ]
  [ "王让定（1962- ），男，博士，宁波大学高等技术研究院教授、博士生导师，主要研究方向为多媒体通信与取证、信息隐藏与隐写分析、智能抄表及传感网络技术等。" ]
  [ "严迪群（1979- ），男，博士，宁波大学信息科学与工程学院副教授、硕士生导师，主要研究方向为多媒体通信、信息安全、基于深度学习的数字语音取证等。" ]
  [ "林昱臻（1994- ），男，宁波大学信息科学与工程学院硕士生，主要研究方向为多媒体通信与信息安全等。" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(U1736215);国家自然科学基金资助项目;The National Natural Science Foundation of China(61672302);浙江省自然科学基金资助项目;The Natural Science Foundation of Zhejiang Province of China;宁波市自然科学基金资助项目;Ningbo Natural Science Foundation of China(2017A610123);宁波大学学科基金资助项目;Ningbo University Fund(XKXL1509);宁波大学学科基金资助项目;Ningbo University Fund(XKXL1503);浙江省移动网应用技术重点实验室开放基金资助项目;Mobile Network Application Technology Key Laboratory of Zhejiang Province(F2018001)
- DOI：10.11959/j.issn.1000-0801.2019071
  中图分类号： TP391
- 网络出版日期：2019-07，
  
  纸质出版日期：2019-07-20
- 稿件说明：
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张雪垣, 王让定, 严迪群, 等. 基于分段STC的音频隐写算法[J]. 电信科学, 2019,35(7):115-123.

Xueyuan ZHANG, Rangding WANG, Diqun YAN, et al. An audio steganography algorithm based on segment-STC[J]. Telecommunications science, 2019, 35(7): 115-123.
张雪垣, 王让定, 严迪群, 等. 基于分段STC的音频隐写算法[J]. 电信科学, 2019,35(7):115-123. DOI： 10.11959/j.issn.1000-0801.2019071.

Xueyuan ZHANG, Rangding WANG, Diqun YAN, et al. An audio steganography algorithm based on segment-STC[J]. Telecommunications science, 2019, 35(7): 115-123. DOI： 10.11959/j.issn.1000-0801.2019071.

摘要

在隐写领域中，STC（syndrome-trellis code）隐写编码是时下最为先进的隐写算法之一。提出了一种基于STC的隐写算法——分段STC。该算法利用分段、局部优化，可有效降低载体失真。首先对音频最低有效位（least significant byte，LSB）载体流进行了分段切割，随后利用最佳子校验矩阵将分段的密信嵌入分段载体中。该隐写算法在现有的语音样本库TIMIT库以及通过网络歌曲自制的样本库上进行了隐写实验。实验结果表明，该思路下的算法可以有效地降低载体的失真元素个数和提高隐写算法的不可检测性。本文算法相较于传统STC算法，失真元素个数的优化程度最高可达到24%；对比同类音频隐写算法，本文算法生成的隐写后音频具备更加优秀的不可感知性能。

Abstract

In steganography field

syndrome-trellis code is a state-of-the-art steganography algorithm. A steganography algorithm of Segment-STC was proposed. Segment-STC could locally optimize the distortion by segmentation. Firstly

the LSB-stream (least significant bit

LSB) of audio cover was segmented as few sub-segments. Then

the segmented message in each sub-segment was embedded to the optimal submatrix. The TIMIT dataset and author collected online songs as databases was used to run the experiments. Results show that segment-STC can effectively reduce the number of distortion elements of cover and improve the undetectability of the stego. Segment-STC algorithm can reduce the distortion over 24%

compared with the original STC algorithm. It also has a better imperceptible performance compare with other similar audio steganography algorithms.

关键词

Keywords

references

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