一种基于LSB序列局部特征的通用隐写检测方法

doi:10.3969/j.issn.0372-2112.2013.02.006

电子学报 ›› 2013, Vol. 41 ›› Issue (2): 239-247.DOI: 10.3969/j.issn.0372-2112.2013.02.006

一种基于LSB序列局部特征的通用隐写检测方法

钟尚平, 徐巧芬, 陈羽中, 何凤英

福州大学数学与计算机科学学院,福建福州 350108

收稿日期:2012-04-23 修回日期:2012-07-19 出版日期:2013-02-25
- 作者简介:
- 钟尚平 男,1969年出生,博士,副教授.主要研究方向为网络信息安全、模式识别等. E-mail:spzhong@fzu.edu.cn 徐巧芬 女,1989年出生,硕士研究生.主要研究方向为多媒体安全、模式识别等.
- 基金资助:
- 国家自然科学基金 (No.61103175); 福建省自然科学基金 (No.2010J01331)

A Universal Steganalysis Method Based on Local Features Extracted from LSB Sequences

ZHONG Shang-ping, XU Qiao-fen, CHEN Yu-zhong, HE Feng-ying

College of Mathematics and Computer Science, Fuzhou University, Fuzhou, Fujian 350108, China

Received:2012-04-23 Revised:2012-07-19 Online:2013-02-25 Published:2013-02-25
- Supported by:
- National Natural Science Foundation of China (No.61103175); Natural Science Foundation of Fujian Province (No.2010J01331)

摘要/Abstract

摘要： 基于短重码间距统计的隐写检测方法对LSB匹配等隐写技术有良好的检测性能.然而该方法为适应不同的应用场合,需要选择适当的短重码维数.这种一元统计分析方法无法考虑多个特征之间存在的联系,从而影响检测能力.本文分析证明了单个短重码间距统计变量的检测能力规律,给出了可减少检测次数的合理选择短重码维数的方法.基于短重码间距统计特征变量之间的相关性选择特征子集,构造局部特征描述向量,进而提出一种基于LSB序列局部特征的通用隐写检测方法.该方法采用GMM生成模型描述多维局部特征,并基于全局序列词汇设计融合GMM生成模型与SVM判别方法的分类器.实验结果表明:本文方法在有效控制虚警率的前提下,对LSB匹配隐写和LSB替换隐写都有较好的检测性能.

关键词: 通用隐写分析, 短重码间距统计, LSB序列, 局部特征, 高斯混合模型, 全局序列词汇

Abstract: The steganalysis method based on spacing statistics of short duplicate code is an efficient universal detection algorithm for LSB matching steganography.But the steganalysis method must select the appropriate dimension of short duplicate code to meet the different applications.This one-dimensionstatistical analysis method could not take into account the links between multivariate statistical features,thus may affect the detection capability.In this paper,a detection capability law of a single short duplicate code statistical feature is proved,and a method to reasonable choice of the short duplicate code dimension is presented to reduce the detection number.By analyzing the correlation between the statistical features of short duplicate code spacing statistics,a selected feature subset is described as a vector of local features.Then,a universal steganalysis method based on local features extracted from LSB sequences is proposed.The proposed steganalysis method uses the Gaussian Mixture Model (GMM) to describe the multi-dimensional local features,and designs classifier by integrating GMM generative model and SVM discriminative method based on global sequence vocabulary.The experimental results show that under the premise of effective control of the false alarm rate,the proposed method achieves the best overall detection performance to LSB matching steganography and to LSB replacement steganography.

Key words: universal steganalysis, spacing statistics of short duplicate code, LSB sequence, local features, Gaussian mixture model, global sequence vocabulary

中图分类号:

TP911.73

钟尚平, 徐巧芬, 陈羽中, 等. 一种基于LSB序列局部特征的通用隐写检测方法[J]. 电子学报, 2013, 41(2): 239-247.

ZHONG Shang-ping, XU Qiao-fen, CHEN Yu-zhong, et al. A Universal Steganalysis Method Based on Local Features Extracted from LSB Sequences[J]. Acta Electronica Sinica, 2013, 41(2): 239-247.

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一种基于LSB序列局部特征的通用隐写检测方法

A Universal Steganalysis Method Based on Local Features Extracted from LSB Sequences

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