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基于MP3的后置式自适应隐写算法
引用本文:张垚,潘峰,申军伟,李宁波. 基于MP3的后置式自适应隐写算法[J]. 计算机科学, 2016, 43(8): 114-117, 153
作者姓名:张垚  潘峰  申军伟  李宁波
作者单位:武警工程大学电子技术系网络与信息安全武警部队重点实验室 西安710086,武警工程大学电子技术系网络与信息安全武警部队重点实验室 西安710086,武警工程大学电子技术系网络与信息安全武警部队重点实验室 西安710086,武警工程大学电子技术系网络与信息安全武警部队重点实验室 西安710086
基金项目:本文受国家科学基金(61379152),陕西省科学基金(2014JQ8358)资助
摘    要:针对MP3隐写算法较为复杂、隐写容量较小的问题,提出一种基于MP3的后置式隐写算法。该算法根据待嵌入秘密信息的多少以及采用Hb码表编码的小值区码字数目的多少,自适应、较均匀且随机地选取嵌入位置,通过改变载体码字的末位实现秘密信息的嵌入。提取信息时无需解码,找到嵌入位置,提取码字的末位从而恢复秘密信息。所提算法在容量方面较MP3stego算法提升约3倍以上,在不可感知性方面较以往采用码字映射的隐写算法提升约10%;另外秘密信息提取时无需解码,大大提高了效率。实验证明了所提算法的安全性、时效性,其能基本满足安全通信的需要。

关 键 词:MP3隐写算法  后置式隐写算法  小值区  自适应  大容量
收稿时间:2015-07-14
修稿时间:2015-11-09

Adaptive Post-type Steganography Algorithm Based on MP3
ZHANG Yao,PAN Feng,SHEN Jun-wei and LI Ning-bo. Adaptive Post-type Steganography Algorithm Based on MP3[J]. Computer Science, 2016, 43(8): 114-117, 153
Authors:ZHANG Yao  PAN Feng  SHEN Jun-wei  LI Ning-bo
Abstract:Aiming at the problem that compressed domain audio steganography algorithm is very complex and has smaller embedding capacity,a kind of post-type algorithm based on MP3 was proposed.This algorithm selectes embedding position adaptively,uniformly and randomly according to the number of secret bits and the number of small-value area groups that use Hb code tables.The algorithm realizes embedding secret information through changing the last bit of carrier-codes.There is no need to decode but only to find the embedding positions and extract the last bit of carrier-codes for extracting secret information.In terms of capacity,the algorithm lifts exceeding three times than classical MP3stego algorithm.In terms of imperceptibility,the algorithm lifts 10% than code-mapping algorithm.In addition,the algorithm greatly improves the efficiency because there is no need to decode.The experimental results prove that the algorithm has the features of safety and timeliness,and can satisfy the need of secure communication.
Keywords:MP3 steganography algorithm  Post-type steganography algorithm  Small-value area  Self-adaptive  Big embedding capacity
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