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A mathematical framework for active steganalysis

R. Chandramouli
2003 Multimedia Systems  
A mathematical framework for steganalysis is presented in this paper with linear steganography being the main focus. A mathematically formal definition of steganalysis is given.  ...  Then, active steganalysis defined as the extraction of a hidden message with little or no a priori information is formulated as blind system identification problem within this framework.  ...  Government is authorized to reproduce and distribute reprints for Governmental purposed notwithstanding any copyright notation thereon.  ... 
doi:10.1007/s00530-003-0101-8 fatcat:msldyyl4jfaljah7hv3hljx6zy

Mathematical approach to steganalysis

Rajarathnam Chandramouli, Edward J. Delp III, Ping W. Wong
2002 Security and Watermarking of Multimedia Contents IV  
A mathematically formal definition of steganalysis is given followed by definitions for passive and active steganalysis.  ...  A mathematical approach to steganalysis is presented in this paper with linear steganography being the main focus.  ...  In this paper, we discuss a mathematical framework for active steganalysis when a certain class of linear steganography algorithms are employed.  ... 
doi:10.1117/12.465273 dblp:conf/sswmc/Chandramouli02 fatcat:yn2vd3ksufc5pkgcfzc3cnl3h4

A Framework Components for Natural Language Steganalysis

Roshidi Din, Azman Samsudin, Puriwat Lertkrai
2012 Journal of clean energy technologies  
In order to have a viable steganalysis method, a steganalysis framework should be developed for natural language.  ...  Thus, the integration of all these components can be known as a framework of natural language steganalysis which in return contribute to the e-application in security environment.  ...  The illustration of this proposed framework for natural language steganalysis is presented in Fig. 3 . III. COMPONENTS OF NATURAL LANGUAGE STEGANALYSIS FRAMEWORK A.  ... 
doi:10.7763/ijcte.2012.v4.548 fatcat:ybwxkzm3afewlfzwjwdi436lsm

Convolution Neural Networks for Blind Image Steganalysis: A Comprehensive Study

Hanaa Mohsin Ahmed, Halah Hasan Mahmoud
2019 Journal of Al-Qadisiyah for Computer Science and Mathematics  
In this comprehensive study a variety of scenarios and efforts are surveyed since 2014 at yet, in order to provide a guide to further improve future researchers what CNN-based blind image steganalysis  ...  Long-standing and important problem in image steganalysis difficulties mainly lie in how to give high accuracy and low payload in stego or cover images for improving performance of the network.  ...  Choosing an activation function for your neural network is a significant consideration because it may impact the way you must format input data.  ... 
doi:10.29304/jqcm.2019.11.2.573 fatcat:rnwnn6q5lbc6xcoucqbmnhtyxm

Steganography capacity: a steganalysis perspective

Rajarathnam Chandramouli, Nasir D. Memon, Edward J. Delp III, Ping W. Wong
2003 Security and Watermarking of Multimedia Contents V  
We propose new definitions for security and capacity in the presence of a steganalyst. The intuition and mathematical notions supporting these definitions are described.  ...  Some numerical examples are also presented to illustrate the need for this investigation.  ...  Government is authorized to reproduce and distribute reprints for Governmental purposed notwithstanding any copyright notation thereon.  ... 
doi:10.1117/12.479732 dblp:conf/sswmc/ChandramouliM03 fatcat:nv4fpnfpovbezay55kifjx5y2m

IMAGE STEGANOGRAPHY AND STEGANALYSIS: CONCEPTS AND PRACTICE [chapter]

Mehdi Kharrazi, Husrev T. Sencar, Nasir Memon
2007 Lecture Notes Series, Institute for Mathematical Sciences, National University of Singapore  
Specifically we establish a framework and define notion of security for a steganographic system.  ...  We also review some of the more recent image steganography and steganalysis techniques.  ...  In a pure steganography framework, the technique for embedding the message is unknown to Wendy and shared as a secret between Alice and Bob.  ... 
doi:10.1142/9789812709066_0005 fatcat:zesucctcbvglfjyjgoapx4leru

Digital image Steganalysis based on Visual Attention and Deep Reinforcement Learning

Donghui Hu, Shengnan Zhou, Qiang Shen, Shuli Zheng, Zhongqiu Zhao, Yuqi Fan
2019 IEEE Access  
First, a region is selected from the image by a visual attention method, and a continuous decision is then made to generate a summary region by reinforcement learning.  ...  In this paper, we propose a new self-seeking steganalysis method based on visual attention and deep reinforcement learning to detect the JPEG-based adaptive steganography.  ...  [30] proposed a novel scheme for constructing effective filters for JPEG steganalysis. As for binary image, Chen et al.  ... 
doi:10.1109/access.2019.2900076 fatcat:4spn7pkjavadvp4kkugzxzdswm

Adaptive Steganalysis Based on Selection Region and Combined Convolutional Neural Networks

Donghui Hu, Qiang Shen, Shengnan Zhou, Xueliang Liu, Yuqi Fan, Lina Wang
2017 Security and Communication Networks  
In this paper, we propose a hybrid approach by designing a region selection method and a new CNN framework.  ...  To evolve more diverse and effective steganalysis features, we design a new CNN framework consisting of three separate subnets with independent structure and configuration parameters and then merge and  ...  [12] proposed a CNN based steganalysis method using Gaussian activation function and 2 Security and Communication Networks in [13] they transfer features generated from a pretrained model to regularize  ... 
doi:10.1155/2017/2314860 fatcat:lvblvbd35zhofpcsnmtu47qaea

Covert Channel Forensics on the Internet: Issues, Approaches, and Experiences

Ashish Patel, M. Shah, Rajarathnam Chandramouli, Koduvayur P. Subbalakshmi
2007 International Journal of Network Security  
The exponential growth of the Internet (WWW in particular) has opened-up several avenues for covert channel communication. Steganographic communication is one such avenue.  ...  In this paper, we discuss various key issues involved in developing a stego (forensic) Web search engine. We also propose approaches to address some of these issues.  ...  Acknowledgement The authors thank the reviewers for helpful comments. This work was supported by a U.S. National Science Foundation grant DAS 0242417.  ... 
dblp:journals/ijnsec/PatelSCS07 fatcat:52i6ngnqdrev3j6r64sp6dxjei

Local-Source Enhanced Residual Network for Steganalysis of Digital Images

Wonhyuk Ahn, Haneol Jang, Seung-Hun Nam, In-Jae Yu, Heung-Kyu Lee
2020 IEEE Access  
and truncated activation functions, and utilizing domain knowledge.  ...  We find batch normalization is an unnecessary module in our framework.  ...  In summary, our main contributions are three-fold: • We propose an LSER, which is a clean end-to-end framework for both spatial and JPEG steganalysis with state-of-the-art performance. • We find batch  ... 
doi:10.1109/access.2020.3011752 fatcat:33s4qxz6b5go5ozjpswwkniry4

Nonparametric Steganalysis of QIM Steganography Using Approximate Entropy

Hafiz Malik, K. P. Subbalakshmi, R. Chandramouli
2012 IEEE Transactions on Information Forensics and Security  
This paper proposes an active steganalysis method for quantization index modulation (QIM)-based steganography.  ...  For a given cover object the decoding error probability depends on embedding rate and decreases monotonically, approaching zero as the embedding rate approaches one.  ...  MESSAGE RECOVERY This section will provide details of the proposed active steganalysis framework. This proposed active steganalysis framework is applicable to QIM-stego images only.  ... 
doi:10.1109/tifs.2011.2169058 fatcat:oop7qgmwdfa3xm4rqr3xqihbh4

A Bayesian image steganalysis approach to estimate the embedded secret message

Aruna Ambalavanan, Rajarathnam Chandramouli
2005 Proceedings of the 7th workshop on Multimedia and security - MM&Sec '05  
We propose a steganalysis approach to estimate the hidden message based on a Bayesian framework, modeling the image as a Markov random field and exploiting the analogy between images and statistical mechanical  ...  Image steganalysis so far has dealt only with detection of a hidden message and estimation of some of its parameters (e.g., message length and secret key).  ...  Acknowledgement This work was supported by a grant from the U.S. Air Force Research Laboratory, Rome, NY.  ... 
doi:10.1145/1073170.1073177 dblp:conf/mmsec/AmbalavananC05 fatcat:e2ndy6p26redjaqlj3nfke5hvm

On the Removal of Steganographic Content from Images

P.P. Amritha, M. Sethumadhavan, R. Krishnan
2016 Defence Science Journal  
However these can be restored to some extent by a deconvolution operation. The finally deconvolved image is subjected to steganalysis to verify the absence of stego content.  ...  Steganography is primarily used for the covert transmission of information even though the purpose can be legitimate or malicious.  ...  Sieffert 7 , et al. explained a framework called stego intrusion detection system.  ... 
doi:10.14429/dsj.66.10797 fatcat:adq2jz4yzjeolak5njtmcfnpxe

StegColNet: Steganalysis based on an ensemble colorspace approach [article]

Shreyank N Gowda, Chun Yuan
2020 arXiv   pre-print
Steganalysis is the process of detecting a steganographic image. We introduce a steganalysis approach that uses an ensemble color space model to obtain a weighted concatenated feature activation map.  ...  average for 0.4 bpc.  ...  The statistical approach searches for mathematical results to determine if the information is being hidden.  ... 
arXiv:2002.02413v2 fatcat:iflbiwscdnaapaajyixqiiydli

CIS-Net: A Novel CNN Model for Spatial Image Steganalysis via Cover Image Suppression [article]

Songtao Wu, Sheng-hua Zhong, Yan Liu, Mengyuan Liu
2019 arXiv   pre-print
Image steganalysis is a special binary classification problem that aims to classify natural cover images and suspected stego images which are the results of embedding very weak secret message signals into  ...  Following such direction, we propose a novel model called Cover Image Suppression Network (CIS-Net), which improves the performance of spatial image steganalysis by suppressing cover image content as much  ...  from input features. lutional layer, a ReLU activation layer and an average pooling To summarize, the proposed CIS-Net uses a series of layer to extract discriminative feature for image steganalysis  ... 
arXiv:1912.06540v1 fatcat:wiinc6uyo5hdldjicpmfwl6p6a
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