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摘要:
The state-of-the-art universal steganalysis method,spatial rich model(SRM),and the steganalysis method using image quality metrics(IQM)are both based on image residuals,while they use 34671 and 10 features respectively.This paper proposes a novel steganalysis scheme that combines their advantages in two ways.First,filters used in the IQM are designed according to the models of the SRM owning to their strong abilities for detecting the content adaptive steganographic methods.In addition,a total variant(TV)filter is also used due to its good performance of preserving image edge properties during filtering.Second,due to each type of these filters having own advantages,the multiple filters are used simultaneously and the features extracted from their outputs are combined together.The whole steganalysis procedure is removing steganographic noise using those filters,then measuring the distances between images and their filtered version with the image quality metrics,and last feeding these metrics as features to build a steganalyzer using either an ensemble classifier or a support vector machine.The scheme can work in two modes,the single filter mode using 9 features,and the multi-filter mode using 639 features.We compared the performance of the proposed method,the SRM and the maxSRMd2.The maxSRMd2 is the improved version of the SRM.The simulated results show that the proposed method that worked in the multi-filter mode was about 10%more accurate than the SRM and maxSRMd2 when the data were globally normalized,and had similar performance with the SRM and maxSRMd2 when the data were locally normalized.
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篇名 A Novel Universal Steganalysis Algorithm Based on the IQM and the SRM
来源期刊 计算机、材料和连续体(英文) 学科 工学
关键词 IMAGE STEGANALYSIS IQM SRM TOTAL VARIATION UNIVERSAL IMAGE STEGANALYSIS
年,卷(期) 2018,(8) 所属期刊栏目
研究方向 页码范围 261-272
页数 12页 分类号 TP3
字数 语种
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IMAGE
STEGANALYSIS
IQM
SRM
TOTAL
VARIATION
UNIVERSAL
IMAGE
STEGANALYSIS
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研究来源
研究分支
研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
计算机、材料和连续体(英文)
月刊
1546-2218
江苏省南京市浦口区东大路2号东大科技园A
出版文献量(篇)
346
总下载数(次)
4
总被引数(次)
0
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