• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.863-867
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• 2021

In this paper, in order to hide the watermark in the LSB of the color image, a color image watermarking technique with high security is proposed by using the adjacent pixels of the image and the spatial encryption technique. According to the technique proposed in this paper, the quality of the stego-image generated by hiding the watermark in the LSB of the color image is so excellent that the difference from the original image cannot be recognized, and the original watermark can be extracted from the stego-image without loss. If the watermark is hidden in the image using the proposed technique, the security of the watermark is maintained very high because the watermark hidden in the stego-image is multi-encrypted. The proposed watermarking technique can be used in applications such as military and intellectual property protection that require high security.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1521-1537
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• 2021

Through information hiding technique, secret message can be hidden in pictures. Stego-image quality and hiding capacity are two important metrics for information hiding. To enhance these metrics, many schemes were proposed by scholars in recent years. Some of them are effective and successful, but there is still a room for further improvement. A high capacity information hiding scheme (PAMO, Pixel-value Adjustment with Modulus Operation Algorithm) is introduced in this paper. PAMO scheme uses pixel value adjustment with modulus operation to hide confidential data in cover-image. PAMO scheme and some referenced schemes are implemented in Python and experiments are carried out to evaluate their performance. In the experiments, PAMO scheme shows better performance than other methods do. When secret message length is less than 72000 bits, the highest hiding capacity of PAMO can reach 7 bits per pixel, at the same time the PSNR of stego-images is greater than 30 dB.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.94-101
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• 2012

This paper proposes an improved image steganalysis scheme to raise the detection rate of stego images out of cover images. To improve the detection rate of stego image in the steganalysis, tiny variation caused by data hiding should be amplified. For this, we extract feature vectors of cover image and stego image by two steps. First, we separate image into upper 4 bit subimage and lower 4 bit subimage. As a result, stego noise is expanded more than two times. We decompose separated subimages into twelve subbands by applying 3-level Haar wavelet transform and calculate co-occurrence probabilities of two different subbands in the same scale. Since co-occurrence probability of the two wavelet subbands is affected by data hiding, it can be used as a feature to differentiate cover images and stego images. The extracted feature vectors are used as the input to the multilayer perceptron(MLP) classifier to distinguish between cover and stego images. We test the performance of the proposed scheme over various embedding rates by the LSB, S-tool, COX's SS, and F5 embedding method. The proposed scheme outperforms the previous schemes in detection rate to existence of hidden message as well as exactness of discrimination.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.395-413
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• 2016

Image authentication is a technique aiming at protecting the integrity of digital images. Reversible image authentication has attracted much attention of researcher because it allows to authenticate tampered regions in the image and to reconstruct the stego image to its original version losslessly. In this paper, we propose a new, reversible image authentication scheme based on adaptive prediction error expansion (PEE) technique. In the proposed scheme, each image block is classified into smooth or complex regions. Then, according to the characteristic of each block, the authentication code is embedded adaptively to achieve high performance of tamper detection. The experimental results demonstrated that the proposed scheme achieves good quality of stego images. In addition, the proposed scheme has ability to reconstruct the stego image to its original version, if no modification is performed on it. Also demonstrated in the experimental results, the proposed scheme provides higher accuracy of tamper detection than state-of-the-art schemes.

• Journal of Korea Multimedia Society
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• v.15 no.7
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• pp.891-902
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• 2012

Reversible data hiding scheme is a form of steganography in which the secret embedding data can be retrieved from a stego image for the purpose of identification, copyright protection and making a covert channel. The reversible data hiding should satisfy that not only are the distortions due to artifacts against the cover image invisible but also it has large embedding capacity as far as possible. In this paper, we propose a robust reversible data hiding scheme by exploiting the differences between a center pixel and its neighboring pixels in each sub-block of the image to embed secret data into extra space. Moreover, our scheme enhances the embedding capacity and can recover the embedded data from the stego image without causing any perceptible distortions to the cover image. Simulation results show that our proposed scheme has lower visible distortions in the stego image and provides robustness to geometrical image manipulations, such as rotation and cropping operations.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.3
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• pp.71-78
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• 2011

This paper propose image steganalysis scheme based on independence between parent and child subband on the multi-layer wavelet domain. The proposed method decompose cover and stego images into 12 subbands by applying 3-level Haar UWT(Undecimated Wavelet Transform), analyze statistical independency between parent and child subband. Because this independency is appeared more difference in stego image than in cover image, we can use it as feature to differenciate between cover and stego image. Therefore we extract 72D features by calculation first 3 order statistical moments from joint characteristic function between parent and child subband. Multi-layer perceptron(MLP) is applied as classifier to discriminate between cover and stego image. We test the performance of proposed scheme over various embedding rates by the LSB, SS, BSS embedding method. The proposed scheme outperforms the previous schemes in detection rate to existence of hidden message as well as exactness of discrimination.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.103-114
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• 2012

The many DE based data hiding schemes and the many data hiding schemes based on Histogram shifting are researched in spatial domain. The data hiding scheme based on Histogram shifting have an advantage of low distortion of the stego image. But the capacity is low than other schemes. On the other hands, the DE based data hiding schemes have an advantage of high capacity. But the quality of the stego image is low. In this paper, new data hiding scheme which has the similar capacity but the increased quality of the stego image is proposed. The prediction error is divided into blocks to embed the secret data in this scheme. The prediction errors in the block are scanned before the secret data is embedded. If one prediction error is low than the threshold at least, the block is changed to embed the secret data. Otherwise the secret data is not embedded. The distortion of the stego image is minimized by this method. But the block that the secret data embedded is marked in location map. So the additional information to extract the secret data and recover the cover image is needed.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.3
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• pp.482-491
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• 2011

The purpose of this study is to design and implement a 2-level secret information transmission system which can be used for information hiding of images transmitted over various IT communication media. To increase the robustness of the hiding power, we combined the steganography method which inserts secret object into cover object to hide the very fact of information hiding itself, and the preprocessing stage to encrypt the secret object before the stego-insertion stage. As a result, even when the stego-image is broken by an attacker, the secret image is protected by encryption. We implemented the 2-level image insertion and extraction algorithm by using C++ programming language. Experiment shows that the PSNR values of stego-images of ours exceed 30.00db which is the threshold of human recognition. The methodology of this study can be applied broadly to the information hiding and protection of the military secret images.

• Journal of Korea Multimedia Society
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• v.24 no.4
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• pp.550-557
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• 2021

Image steganalysis is a technique for detecting images with steganographic algorithms applied, called stego images. With state-of-the-art CNN-based steganalysis methods, we can detect stego images with high accuracy, but it is not possible to know which steganographic algorithm is used. Identifying stego images is essential for extracting embedded data. In this paper, as the first step for extracting data from stego images, we propose a hierarchical CNN structure for senary classification of steganographic algorithms. The hierarchical CNN structure consists of multiple CNN networks which are trained to classify each steganographic algorithm and performs binary or ternary classification. Thus, it classifies multiple steganogrphic algorithms hierarchically and stepwise, rather than classifying them at the same time. In experiments of comparing with several conventional methods, including those of classifying multiple steganographic algorithms at the same time, it is verified that using the hierarchical CNN structure can greatly improve the classification accuracy.