计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (34): 162-164.

• 网络、通信与安全 • 上一篇    下一篇

基于小波包统计量的音频隐秘检测算法

宋 坤,杨晓元,刘 佳,潘 峰   

  1. 武警工程学院 电子技术系 网络与信息安全武警部队重点实验室,西安 710086
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-12-01 发布日期:2007-12-01
  • 通讯作者: 宋 坤

Detection algorithm of audio steganography based on wavelet packet statistics

SONG Kun,YANG Xiao-yuan,LIU Jia,PAN Feng   

  1. Key Laboratory of Network and Information Security Engineering,College of the APF,Xi’an 710086,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-12-01 Published:2007-12-01
  • Contact: SONG Kun

摘要: 提出了一种基于小波包分解和多类支持向量机分类的音频隐秘检测算法,该算法首先对音频文件进行小波包分解,然后根据小波分解系数绝对值和绝对值线性预测的误差生成特征向量,并采用多类支持向量机进行模式分类。在不同嵌入率下对几种常见的隐秘软件生成的隐秘音频进行仿真试验,结果表明,该算法具有较强的通用性,对于隐密音频文件具有较高的识别率。

关键词: 多类支持向量机, 小波包分解, 隐密音频检测

Abstract: A new detection of steganography algorithm based on wavelet statistics of audio and multi-class SVM is proposed.In this algorithm,wavelet packet decompision is implemented to audio files,the magnitude of decomposition coefficients and the error between the actual coefficient and the predicted coefficient magnitudes are used to yield statistics.The multi-class support vector machine algorithm has been employed in the pattern discrimination.Stego audios created by several tools are tested under different embed rates.The experimental results show that the algorithm has stronger universal performance and higher discriminating rate.

Key words: multi-class SVM, wavelet packet decomposition, dection of steganography audio