• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3778-3793
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• 2019

Image steganography is one of the key types of steganography where a message to be sent is hidden inside the cover image. The most commonly used techniques for image steganography rely on LSB steganography. In this paper, a novel image steganography technique based on blocks matrix determinant method is proposed. Under this method, a cover image is divided into blocks of size $2{\times}2$ pixels and the determinant of each block is calculated. The comparison of the determinant values and corresponding data bits yields a delicate way for the embedment of data bits. The main aim of the proposed technique is to ensure concealment of secret data inside an image without affecting the cover image quality. When the proposed steganography method is compared with other existing LSB steganography methods, it is observed that it not only provides higher PSNR, lower MSE but also guarantees better quality of the stego image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1078-1099
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• 2021

Traditional image steganography hides secret information by embedding, which inevitably leaves modification traces and is easy to be detected by steganography analysis tools. Since coverless steganography can effectively resist steganalysis, it has become a hotspot in information hiding research recently. Most coverless image steganography (CIS) methods are based on mapping rules, which not only exposes the vulnerability to geometric attacks, but also are less secure due to the revelation of mapping rules. To address the above issues, we introduced camouflage images for steganography instead of directly sending stego-image, which further improves the security performance and information hiding ability of steganography scheme. In particular, based on the different sub-features of stego-image and potential camouflage images, we try to find a larger similarity between them so as to achieve the reversible steganography. Specifically, based on the existing CIS mapping algorithm, we first can establish the correlation between stego-image and secret information and then transmit the camouflage images, which are obtained by reversible sub-feature retrieval algorithm. The received camouflage image can be used to reverse retrieve the stego-image in a public image database. Finally, we can use the same mapping rules to restore secret information. Extensive experimental results demonstrate the better robustness and security of the proposed approach in comparison to state-of-art CIS methods, especially in the robustness of geometric attacks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1228-1248
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• 2020

Steganalysis & steganography have witnessed immense progress over the past few years by the advancement of deep convolutional neural networks (DCNN). In this paper, we analyzed current research states from the latest image steganography and steganalysis frameworks based on deep learning. Our objective is to provide for future researchers the work being done on deep learning-based image steganography & steganalysis and highlights the strengths and weakness of existing up-to-date techniques. The result of this study opens new approaches for upcoming research and may serve as source of hypothesis for further significant research on deep learning-based image steganography and steganalysis. Finally, technical challenges of current methods and several promising directions on deep learning steganography and steganalysis are suggested to illustrate how these challenges can be transferred into prolific future research avenues.

• Journal of Broadcast Engineering
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• v.23 no.4
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• pp.462-473
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• 2018

Steganography is to hide information in a media data so naturally that the other users can not notice the existence of hidden information. Data encryption focuses on the complex encoding methods of information data in order to make it difficult to decode the information even though the other users notice the existence of information. On the other hand, steganography methods concentrate on natural hiding information into other media. Since the other users do not recognize the existence of hidden information, the information can be better protected. This paper introduces the concept of image steganography that an image information is concealed into another image (cover image), and proposes a new discrimination method of steganography. This paper explains the spatial methods with LSB manipulation and frequency methods using DCT coefficients. Finally, this paper proposes a new discrimination method of image steganography by inspecting that an image information is correctly decoded.

• Journal of information and communication convergence engineering
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• v.15 no.3
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• pp.151-159
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• 2017

Steganography, which is popular as an image processing technology, is the art of using digital images to hide a secret message in such a way that its existence can only be discovered by the sender and the intended receiver. This technique has the advantage of concealing secret information in a cover medium without drawing attention to it, unlike cryptography, which tries to convert data into something messy or meaningless. In this paper, we propose two efficient least significant bit (LSB)-based steganography techniques for designing an image-based steganography system on chip using hardware description language (HDL). The proposed techniques manipulate the LSB plane of the cover image to embed text inside it. The output of these algorithms is a stego-image which has the same quality as that of the original image. We also implement the proposed techniques using the Altera field programmable gate array (FPGA) and Quartus II design software.

• ETRI Journal
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• v.36 no.3
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• pp.479-489
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• 2014

This paper presents a model-based image steganography method based on Watson's visual model. Model-based steganography assumes a model for cover image statistics. This approach, however, has some weaknesses, including perceptual detectability. We propose to use Watson's visual model to improve perceptual undetectability of model-based steganography. The proposed method prevents visually perceptible changes during embedding. First, the maximum acceptable change in each discrete cosine transform coefficient is extracted based on Watson's visual model. Then, a model is fitted to a low-precision histogram of such coefficients and the message bits are encoded to this model. Finally, the encoded message bits are embedded in those coefficients whose maximum possible changes are visually imperceptible. Experimental results show that changes resulting from the proposed method are perceptually undetectable, whereas model-based steganography retains perceptually detectable changes. This perceptual undetectability is achieved while the perceptual quality - based on the structural similarity measure - and the security - based on two steganalysis methods - do not show any significant changes.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.83-93
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• 2021

COVID-19 poses a major risk to global health, highlighting the importance of faster and proper diagnosis. To handle the rise in the number of patients and eliminate redundant tests, healthcare information exchange and medical data are transmitted between healthcare centres. Medical data sharing helps speed up patient treatment; consequently, exchanging healthcare data is the requirement of the present era. Since healthcare professionals share data through the internet, security remains a critical challenge, which needs to be addressed. During the COVID-19 pandemic, computed tomography (CT) and X-ray images play a vital part in the diagnosis process, constituting information that needs to be shared among hospitals. Encryption and image steganography techniques can be employed to achieve secure data transmission of COVID-19 images. This study presents a new encryption with the image steganography model for secure data transmission (EIS-SDT) for COVID-19 diagnosis. The EIS-SDT model uses a multilevel discrete wavelet transform for image decomposition and Manta Ray Foraging Optimization algorithm for optimal pixel selection. The EIS-SDT method uses a double logistic chaotic map (DLCM) is employed for secret image encryption. The application of the DLCM-based encryption procedure provides an additional level of security to the image steganography technique. An extensive simulation results analysis ensures the effective performance of the EIS-SDT model and the results are investigated under several evaluation parameters. The outcome indicates that the EIS-SDT model has outperformed the existing methods considerably.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.3
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• pp.29-36
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• 2015

Steganography is the technique of hiding the existence of a secret message that is communicated hiddenly. Generally, the main objectives of this paper is to develop newer and more sophisticated steganographic techniques based on perceptual transparency, robustness and capacity of the hidden data. This paper analyzes the advantages and disadvantages of image steganography techniques and proposes an effective method. As a result, the images steganography technique based on good ELSB and DCT which applies the rearranged key is secure and effective.

• Journal of the Optical Society of Korea
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• v.12 no.3
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• pp.136-146
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• 2008

We proposed an adaptive steganography of an optical image using bit-planes and multichannel characteristics. The experiment's purpose was to compare the most popular methods used in optical steganography and to examine their advantages and disadvantages. In this paper we describe two digital methods: the first uses less significant bits(LSB) to encode hidden data, and in the other all blocks of $n{\times}n$ pixels are coded by using DCT(Digital Cosine Transformation), and two optical methods: double phase encoding and digital hologram watermarking with double binary phase encoding by using IFTA(Iterative Fourier Transform Algorithm) with phase quantization. Therefore, we investigated the complexity on bit plane and data, similarity insert information into bit planes. As a result, the proposed method increased the insertion capacity and improved the optical image quality as compared to fixing threshold and variable length method.

• Journal of Korea Multimedia Society
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• v.8 no.3
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• pp.379-388
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• 2005

Image steganography Is a secret communication scheme to transmit a secret message, which is embedded into an image. The original image and the embedded image are called the cover image and the stego image, respectively. In other words, a sender embeds a secret message into a cover image and transmits a stego image to a receiver, while the receiver takes the stego image, extracts the message from it, and reads the message. General requirements for steganography are great capacity of secret messages, imperceptibility of stego images, and confidentiality between a sender and a receiver. In this paper, we propose a method for being satisfied with three requirements. In order to hide a secret message into a cover image safely, we use a difference value of two consecutive pixels and a secret quantization range. The former is used for the imperceptibility and the latter for the confidentiality. Furthermore, the number of insertion bits is changed according to the difference value for the imperceptibility. Through experiments, we have shown that our method is more good quality of stego images than many other related methods and increases the amount o( message insertion by performing dual insertion processing for some pixels.