电信科学 ›› 2019, Vol. 35 ›› Issue (7): 115-123.doi: 10.11959/j.issn.1000-0801.2019071

• 研究与开发 • 上一篇    下一篇

基于分段STC的音频隐写算法

张雪垣,王让定,严迪群,林昱臻   

  1. 宁波大学信息科学与工程学院,浙江 宁波 315211
  • 修回日期:2019-04-20 出版日期:2019-07-20 发布日期:2019-07-22
  • 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。
  • 基金资助:
    国家自然科学基金资助项目(U1736215);国家自然科学基金资助项目(61672302);浙江省自然科学基金资助项目;宁波市自然科学基金资助项目(2017A610123);宁波大学学科基金资助项目(XKXL1509);宁波大学学科基金资助项目(XKXL1503);浙江省移动网应用技术重点实验室开放基金资助项目(F2018001)

An audio steganography algorithm based on segment-STC

Xueyuan ZHANG,Rangding WANG,Diqun YAN,Yuzhen LIN   

  1. College of Information Science and Engineering, Ningbo University, Ningbo 315211, China
  • Revised:2019-04-20 Online:2019-07-20 Published:2019-07-22
  • Supported by:
    The National Natural Science Foundation of China(U1736215);The National Natural Science Foundation of China(61672302);The Natural Science Foundation of Zhejiang Province of China;Ningbo Natural Science Foundation of China(2017A610123);Ningbo University Fund(XKXL1509);Ningbo University Fund(XKXL1503);Mobile Network Application Technology Key Laboratory of Zhejiang Province(F2018001)

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。

关键词: 分段STC, 载体密信分配, 最佳子校验矩阵, WAV隐写

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.

Key words: segment-STC, cover-message allocation, optimal submatrix, WAV steganography

中图分类号: 

No Suggested Reading articles found!