An Improved Steganalysis Method Using Feature Combinations

2019 ◽  
pp. 115-127 ◽  
Author(s):  
Zichi Wang ◽  
Zhenxing Qian ◽  
Xinpeng Zhang ◽  
Sheng Li
Keyword(s):  
Steganalysis Method

Effective Recognition of Stereo Image Concealed Media of Interpolation Error with Difference Expansion

2016 ◽  
pp. 157-165
Author(s):  
Hemalatha J. ◽  
Kavitha Devi M. K.
Keyword(s):  
Support Vector Machine ◽  
Reversible Data Hiding ◽  
Stereo Image ◽  
Interpolation Error ◽  
Support Vector ◽  
Histogram Shifting ◽  
Difference Expansion ◽  
Statistical Feature ◽  
High Payload ◽  
Steganalysis Method

In this chapter, a new data conceal technique is anticipated for digital images. The method computes the interpolation error of the image by using histogram shifting method and difference expansion. With the expectation of embedding high payload and less distortion, the undisclosed data has embedded in the interpolating error. Additionally for hiding the data, reversible data hiding technique is used. The histogram deviation is used as evidence for resulting the data conceal in the stereo images. To our best knowledge, by extracting the statistical feature from the image subsample works as steganalysis scheme. To enhance the revealing rate precision the well known support vector machine acts as classifier. In addition to that the experimental results show that the proposed steganalysis method has enhanced the detection exactness of the stego images.

scholarly journals A Linguistic Steganalysis Approach Base on Source Features of Text and Immune Mechanism

2017 ◽  
Vol 10 (4) ◽  
pp. 60
Author(s):  
Licai Zhu
Keyword(s):  
Statistical Features ◽  
Immune Mechanism ◽  
Hidden Information ◽  
Detection Mechanism ◽  
Is Success ◽  
Plain Text ◽  
Segment Size ◽  
Challenge Area ◽  
Blind Steganalysis ◽  
Steganalysis Method

Linguistic steganalysis is a technique that discovering potentially hidden information embedded through using linguistically in plain text using. Varieties of syntax and multi-meanings of semantics for linguistics augment the difficulty of linguistic steganalysis intensely, thereby it is a challenge area. In this paper, we propose a novel steganalysis method for linguistics based on immune. This method has two attributions: i). basis statistical features of text are employed for blind steganalysis ii). immune technique is chosen to build a two-level detection mechanism to detect two categories of stego text respectively, one of which is Success-Stego-text and another is False-Stego-text. Appropriate detections are generated and preferable features are signed. Experiments prove the approach has higher accuracy than current steganalysis algorithms. Especially when the segment size of text is greater than 3kB, the accuracies of detecting for natural text and stego text are both more than 95%. 

Study on Universal Steganalysis for BMP Images Based on Multi-Domain Features

2013 ◽  
Vol 278-280 ◽  
pp. 1906-1909 ◽  
Author(s):  
Yan Yan ◽  
Li Ting Li ◽  
Jian Bin Xue ◽  
Hong Guo Liu ◽  
Qiu Yu Zhang
Keyword(s):  
Information Security ◽  
Digital Images ◽  
Spatial Domain ◽  
New Method ◽  
Research Issue ◽  
Important Research ◽  
High Complexity ◽  
Universal Steganalysis ◽  
Steganalysis Method

Steganslysis is an important research issue in information security. Aimed at the most commonly used cover media, digital images, the paper proposed a new method of universal steganalysis method based on multi-domain features. Features were extracted from spatial domain and DWT domain to overcome the drawbacks of steganslysis algorithm for specific steganography, such as high complexity and low correct detecting ratio. Experiment results show that the proposed algorithm can solve the low detecting problem and achieve a better reliability on low embedding rates.

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