• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.193-196
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• 2008

In this paper a detail study of existing steganographic methods are presented. An example is given of LSB substitution with uncompressed domain i.e., BMP image. In case of compressed domain JPEG image steganography is presented. Almost all popular steganographic algorithms, such as JPEG JSteg, F3, F4 and Selective Block Steganography (SBS) are described. The applications of steganographic methods are also presented briefly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.366-381
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• 2020

Steganography has been successfully employed in various applications, e.g., copyright control of materials, smart identity cards, video error correction during transmission, etc. Deep learning-based steganography models can hide information adaptively through network learning, and they draw much more attention. However, the capacity, security, and robustness of the existing deep learning-based steganography models are still not fully satisfactory. In this paper, three models for different cases, i.e., a basic model, a secure model, a secure and robust model, have been proposed for different cases. In the basic model, the functions of high-capacity secret information hiding and extraction have been realized through an encoding network and a decoding network respectively. The high-capacity steganography is implemented by hiding a secret image into a carrier image having the same resolution with the help of concat operations, InceptionBlock and convolutional layers. Moreover, the secret image is hidden into the channel B of carrier image only to resolve the problem of color distortion. In the secure model, to enhance the security of the basic model, a steganalysis network has been added into the basic model to form an adversarial network. In the secure and robust model, an attack network has been inserted into the secure model to improve its robustness further. The experimental results have demonstrated that the proposed secure model and the secure and robust model have an overall better performance than some existing high-capacity deep learning-based steganography models. The secure model performs best in invisibility and security. The secure and robust model is the most robust against some attacks.

• Current Optics and Photonics
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• v.8 no.3
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• pp.270-281
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• 2024

Information-hiding technology is introduced into an optical ghost imaging encryption scheme, which can greatly improve the security of the encryption scheme. However, in the current mainstream research on camouflage ghost imaging encryption, information hiding techniques such as digital watermarking can only hide 1/4 resolution information of a cover image, and most secret images are simple binary images. In this paper, we propose an equal-resolution image-hiding encryption scheme based on deep learning and computational ghost imaging. With the equal-resolution image steganography network based on deep learning (ERIS-Net), we can realize the hiding and extraction of equal-resolution natural images and increase the amount of encrypted information from 25% to 100% when transmitting the same size of secret data. To the best of our knowledge, this paper combines image steganography based on deep learning with optical ghost imaging encryption method for the first time. With deep learning experiments and simulation, the feasibility, security, robustness, and high encryption capacity of this scheme are verified, and a new idea for optical ghost imaging encryption is proposed.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.143-151
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• 2021

The enormous prevalence of transferring official confidential digital documents via the Internet shows the urgent need to deliver confidential messages to the recipient without letting any unauthorized person to know contents of the secret messages or detect there existence . Several Steganography techniques such as the least significant Bit (LSB), Secure Cover Selection (SCS), Discrete Cosine Transform (DCT) and Palette Based (PB) were applied to prevent any intruder from analyzing and getting the secret transferred message. The utilized steganography methods should defiance the challenges of Steganalysis techniques in term of analysis and detection. This paper presents a novel and robust framework for color image steganography that combines Linear Congruential Generator (LCG), simulated annealing (SA), Cesar cryptography and LSB substitution method in one system in order to reduce the objection of Steganalysis and deliver data securely to their destination. SA with the support of LCG finds out the optimal minimum sniffing path inside a cover color image (RGB) then the confidential message will be encrypt and embedded within the RGB image path as a host medium by using Cesar and LSB procedures. Embedding and extraction processes of secret message require a common knowledge between sender and receiver; that knowledge are represented by SA initialization parameters, LCG seed, Cesar key agreement and secret message length. Steganalysis intruder will not understand or detect the secret message inside the host image without the correct knowledge about the manipulation process. The constructed system satisfies the main requirements of image steganography in term of robustness against confidential message extraction, high quality visual appearance, little mean square error (MSE) and high peak signal noise ratio (PSNR).

• Journal of Information Processing Systems
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• v.10 no.2
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• pp.256-270
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• 2014

A new morphed steganographic algorithm is proposed in this paper. Image security is a challenging problem these days. Steganography is a method of hiding secret data in cover media. The Least Significant Bit is a standard Steganographic method that has some limitations. The limitations are less capacity to hide data, poor stego image quality, and imperceptibility. The proposed algorithm focuses on these limitations. The morphing concept is being used for image steganography to overcome these limitations. The PSNR and standard deviation are considered as a measure to improve stego image quality and morphed image selection, respectively. The stego keys are generated during the morphed steganographic embedding and extracting process. Stego keys are used to embed and extract the secret image. The experimental results, which are based on hiding capacity and PSNR, are presented in this paper. Our research contributes towards creating an improved steganographic method using image morphing. The experimental result indicates that the proposed algorithm achieves an increase in hiding capacity, stego image quality, and imperceptibility. The experimental results were compared with state of the art steganographic methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5592-5609
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• 2017

JPEG steganography detection is an active research topic in the field of information hiding due to the wide use of JPEG image in social network, image-sharing websites, and Internet communication, etc. In this paper, a new steganalysis method for content-adaptive JPEG steganography is proposed by integrating the evolutionary feature selection and classifier ensemble selection. First, the whole framework of the proposed steganalysis method is presented and then the characteristic of the proposed method is analyzed. Second, the feature selection method based on genetic algorithm is given and the implement process is described in detail. Third, the method of classifier ensemble selection is proposed based on Pareto evolutionary optimization. The experimental results indicate the proposed steganalysis method can achieve a competitive detection performance by compared with the state-of-the-art steganalysis methods when used for the detection of the latest content-adaptive JPEG steganography algorithms.

• Journal of Korea Multimedia Society
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• v.7 no.7
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• pp.913-921
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• 2004

Steganography is a kind of data hiding which can hide secret information to digital media. It is performed so that another person does not recognize any information and make secret communication between each other. Specially, it is not easy to hide secret information without being visually recognized in scanned text image or cartoon image etc. In this paper, we propose an improved method that can embed a large quantity of secret information in a binary image without noticeable artifacts. Binary cartoon image is divided into block of 3-by-3 sizes. Secret information is embedded by using run-length of 8-neighborhood pixels except for the center pixel of the block. To improve the embedding capacity, we embed it into center pixel under to some condition.

• Journal of Korea Multimedia Society
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• v.8 no.7
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• pp.961-973
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• 2005

In this paper, we proposed an adaptive steganography of color image using bit-planes and multichannel characteristics. Applying fixing threshold, if we insert information into all bit-planes of RGB channel, each channels showed different image quality. Therefore, we first defined the channel weight and the bit-plane weight to solve the fixing threshold problem of BPCS (bit-plane complexity steganography) method. We then proposed a new adaptive threshold method using the bit-plane weight of channels and the bit-plane complexity of cover image to increase insertion capacity adaptively In the experiment, we inserted information into the color images with the same image quality and same insertion capacity, and we analyzed the Insertion capacity and image quality. As a result, the proposed method increased the insertion capacity and improved the image quality than BPCS method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3298-3321
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• 2021

A lot of data hiding schemes have been proposed to embed secret data in the plain cover images or compressed images of various formats, including JPEG, AMBTC, VQ, etc. In this paper, we propose a production process of mosaic images based on three regular images of coffee beans. A primary image is first mimicked by the process to produce a mosaic cover image. A two-layer steganography is applied to hide secret data in the mosaic image. Based on the low visual quality of the mosaic cover image, its PSNR value can be improved about 1.5 dB after embedding 3 bpp. This is achieved by leveraging the newly proposed polarized search mask and the concepts of strong embedding and weak embedding. Applying steganography to the mosaic cover images is a completely new idea and it is promising.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.73-82
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• 2022

This paper shows the hiding process of unlimited secret text size in an image using three methods: the first method is the traditional method in steganography that based on the concealing the binary value of the text using the least significant bits method, the second method is a new method to hide the data in an image based on Exclusive OR process and the third one is a new method for hiding the binary data of the text into an image (that may be grayscale or RGB images) using Exclusive and Huffman Coding. The new methods shows the hiding process of unlimited text size (data) in an image. Peak Signal to Noise Ratio (PSNR) is applied in the research to simulate the results.