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A Novel Approach Based on Modified Cycle Generative Adversarial Networks for Image Steganography

P G Kuppusamy, K C Ramya, S Sheebha Rani, M Sivaram, Vigneswaran Dhasarathan
2020 Scalable Computing : Practice and Experience  
To overcome this issue, in this paper, we are proposing to use generative adversarial networks for image steganography which include discriminative models to identify steganography image during training  ...  The proposed modified cycle Generative Adversarial Networks (Mod Cycle GAN) algorithm is tested using the USC-SIPI database and the experimentation results were better when compared with the algorithms  ...  We have studied about various existing image steganographic algorithm present in the literature and came up with a new approach of modified cycle GAN for robust image steganography.  ... 
doi:10.12694/scpe.v21i1.1613 fatcat:25daf7gmkreepi3hsu6nstvgyu

A Steganography Algorithm Based on CycleGAN for Covert Communication in the Internet of Things

Ruohan Meng, Qi Cui, Zhili Zhou, Zhangjie Fu, Xingming Sun
2019 IEEE Access  
In order to make sure secure communications, this paper proposes a novel steganography algorithm based on image-to-image translation by adding steganography module and steganalysis module to CycleGAN,  ...  Steganalysis network is used to improve the anti-detection ability of stego image. Moreover, cycle consistent in CycleGAN can guarantee the quality of the generated image.  ...  [28] put forward the ''pix2pix'' framework by modifying conditional adversarial networks. The framework added a U-Net structure to the generator.  ... 
doi:10.1109/access.2019.2920956 fatcat:iw7cli6kgrbsfbpqz62mkw7mqe

Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganography [article]

Olivia Byrnes, Wendy La, Hu Wang, Congbo Ma, Minhui Xue, Qi Wu
2021 arXiv   pre-print
This survey summarises recent developments in deep learning techniques for data hiding for the purposes of watermarking and steganography, categorising them based on model architectures and noise injection  ...  Data hiding is the process of embedding information into a noise-tolerant signal such as a piece of audio, video, or image.  ...  HiDDeN [96] uses a novel embedding strategy based on adversarial examples.  ... 
arXiv:2107.09287v1 fatcat:2sqcyzv6t5ccdiffk5cmag7tya

Image Steganography: A Review of the Recent Advances

Nandhini Subramanian, Omar Elharrouss, Somaya Al-Maadeed, Ahmed Bouridane
2021 IEEE Access  
Though research on steganography is quite recent, it has benefited from DL methods including convolutional Neural Networks (CNNs) Generative Adversarial Networks (GANs) based methods and their deployment  ...  The existing methods used for image steganography using a GAN architecture can be grouped into five categories -a three network based GAN model, cycle-GAN based architectures, sender-receiver architecture  ... 
doi:10.1109/access.2021.3053998 fatcat:obezfqxgivg43mugsmmcxdceri

Adversarial Embedding: A robust and elusive Steganography and Watermarking technique [article]

Salah Ghamizi, Maxime Cordy, Mike Papadakis, Yves Le Traon
2019 arXiv   pre-print
We propose adversarial embedding, a new steganography and watermarking technique that embeds secret information within images.  ...  The key idea of our method is to use deep neural networks for image classification and adversarial attacks to embed secret information within images.  ...  Our objective is to pave the way for a new generation of watermarking and steganography techniques relying on adversarial ML.  ... 
arXiv:1912.01487v1 fatcat:qw7i3bguobbqbkq5yhopgvvhla

Combining Cryptography with Steganography

Muharrem Tuncay Gençoğlu, A. Atangana, H. Bulut, Z. Hammouch, H.M. Baskonus, T. Mekkaoui, F. Bin Muhammad Belgacem
2017 ITM Web of Conferences  
For more security we used iris image of authorized person to hide encrypted data. The keys required for BLOWFISH algorithm is generated from same iris image.  ...  This paper presents two level data security in Network system. Cryptographic algorithm BLOWFISH and Steganography algorithm List significant Bit (LSB) are used for data security.  ...  [7] "Multilevel Network Security Based on Iris Biometric", In this paper A novel security Mechanism is developed here for high security networks by combining IRIS biometric techniques with cryptographic  ... 
doi:10.1051/itmconf/20171301010 fatcat:ycwvh4dxqrd5fg6t5cezbkhqfy

Self-Contained Stylization via Steganography for Reverse and Serial Style Transfer [article]

Hung-Yu Chen, I-Sheng Fang, Wei-Chen Chiu
2020 arXiv   pre-print
Therefore, in this paper we advance to keep the content information of the input image during the process of style transfer by the power of steganography, with two approaches proposed: a two-stage model  ...  We conduct extensive experiments to successfully verify the capacity of our models, in which both of them are able to not only generate stylized images of quality comparable with the ones produced by typical  ...  We are grateful to the National Center for Highperformance Computing for computer time and facilities.  ... 
arXiv:1812.03910v3 fatcat:ndowt5uirzgr3lhfqcjr626fqi

A Survey of Image Information Hiding Algorithms Based on Deep Learning

Ruohan Meng, Qi Cui, Chengsheng Yuan
2018 CMES - Computer Modeling in Engineering & Sciences  
At present, the model based on deep learning is also widely applied to the field of information hiding. This paper makes an overall conclusion on image information hiding based on deep learning.  ...  It is divided into four parts of steganography algorithms, watermarking embedding algorithms, coverless information hiding algorithms and steganalysis algorithms based on deep learning.  ...  [Volkhonskiy, Nazarov, Borisenko et al. (2017)] propose SGAN (Steganographic Generative Adversarial Networks), mainly adding a discriminator that is steganalysis based on GAN.  ... 
doi:10.31614/cmes.2018.04765 fatcat:tvmits2gdrb4xesfswtr275wpy

Image Steganography Using Deep Neural Networks

Kavitha Chinniyan, Thamil Vani Samiyappan, Aishvarya Gopu, Narmatha Ramasamy
2022 Intelligent Automation and Soft Computing  
Steganography is the technique of hiding secret data within ordinary data by modifying pixel values which appear normal to a casual observer.  ...  The proposed work consists of multiple networks which are trained with Flickr Image Dataset and results in Secret Image with a Loss of 4% and Container Image with a Loss of 14%.  ...  [11] proposed Generative Adversarial Networks (GAN) model which can completely hide a gray secret image into a RGB cover image of same size.  ... 
doi:10.32604/iasc.2022.027274 fatcat:cipnmykqnngchpcid3wt7d4q5a

Generative Models for Security: Attacks, Defenses, and Opportunities [article]

Luke A. Bauer, Vincent Bindschaedler
2021 arXiv   pre-print
Generative models learn the distribution of data from a sample dataset and can then generate new data instances.  ...  In particular, we discuss the use of generative models in adversarial machine learning, in helping automate or enhance existing attacks, and as building blocks for defenses in contexts such as intrusion  ...  For example, when generative models are used for image-based steganography (Section 7), the goal of the evaluation methodology may be to quantify the ability of an adversary to distinguish between images  ... 
arXiv:2107.10139v2 fatcat:wjb4dcdpvveztd2h4aretus56a

An Epistemological Approach to Steganography [chapter]

Rainer Böhme
2009 Lecture Notes in Computer Science  
An introduction to the epistemological perspective on steganography is given along with a structured discussion on how the novel perspective fits into the existing body of literature.  ...  Steganography has been studied extensively in the light of information, complexity, probability and signal processing theory.  ...  Acknowledgements The author wants to thank Andrew Ker and Matthias Kirchner for their useful comments on earlier versions of this work.  ... 
doi:10.1007/978-3-642-04431-1_2 fatcat:2hc4q3begjdnnobf6qpu4prm4a

Pixel Indicator Technique for RGB Image Steganography

Adnan Abdul-Aziz Gutub
2010 Journal of Emerging Technologies in Web Intelligence  
steganography in color and gray-scale images’, IEEE [5] Westfeld A., 'Steganography for Radio Amateurs— Multimedia Special Issue on Security, pp. 22-28, A DSSS Based Approach for  ...  existence of data in transmission or to hide data on the network in case of a the other two channels.  ... 
doi:10.4304/jetwi.2.1.56-64 fatcat:rze53qyxtrglfotb3etlhyzcxu

Stegomalware: A Systematic Survey of MalwareHiding and Detection in Images, Machine LearningModels and Research Challenges [article]

Rajasekhar Chaganti, Vinayakumar Ravi, Mamoun Alazab, Tuan D. Pham
2021 arXiv   pre-print
Based on our findings, we perform the detail review of the image steganography techniques including the recent Generative Adversarial Networks (GAN) based models and the image steganalysis methods including  ...  But the malware payload hiding in multimedia using steganography detection has been a challenge for enterprises, as these are rarely seen and usually act as a stager in sophisticated attacks.  ...  [90] proposed a SGAN network to generate the steganographic images.  ... 
arXiv:2110.02504v1 fatcat:wz5hnqeixrcdjc4afoyycjp7ui

Analysis of Security Threats in Wireless Sensor Network

Sahabul Alam, Debashis De
2014 International Journal of Wireless & Mobile Networks  
In this paper we have explored general security threats in wireless sensor network with extensive study.  ...  Wireless Sensor Network(WSN) is an emerging technology and explored field of researchers worldwide in the past few years, so does the need for effective security mechanisms.  ...  In steganography a message embeds into the multimedia data(image,sound,video etc.).Steganography modifies the carrier in a way that is not perceptible and looks just like ordinary.  ... 
doi:10.5121/ijwmn.2014.6204 fatcat:sp4zlljusngtvgd7w4azalimvm

High-Capacity Image Steganography Based on Improved FC-DenseNet

Xintao Duan, Liu Nao, Gou Mengxiao, Dongli Yue, Zimei Xie, Yuanyuan Ma, Chuan Qin
2020 IEEE Access  
Currently, based on the method of modifying the carrier image [4] - [6] , it mainly includes modifying the spatial domain of the image and modifying the frequency domain of the image.  ...  In the generative adversarial network of [9] and [10] , the stego-image image generated by the generator makes the discriminator unable to distinguish between the carrier image and the stego-image.  ... 
doi:10.1109/access.2020.3024193 fatcat:qt4kehgypba5lozvu3cwrwmnyy
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