• 한국멀티미디어학회논문지
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• 제8권3호
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• pp.379-388
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• 2005

화상 심층암호(image steganography)는 비밀 정보를 화상에 몰래 숨겨 송/수신자간에 주고받는 비밀 통신의 한 방법이다. 송신자는 특별한 의미를 갖지 않는 커버 화상(cover image)에 비밀 정보를 삽입한 스테고 화상을 수신자에게 전달한다. 수신자는 송신자에게 받은 스테고 화상(stego image)에서 숨겨진 비밀 정보를 추출하여 그 개용을 확인한다. 본 논문에서는 알고리즘이 간단하면서, 심층암호의 필수 조건인 비밀 정보의 삽입용량, 스테고 화상의 비가시성, 그리고 송i수신자간의 기밀성을 모두 만족할 수 있는 기법들을 제안한다 제안 방식은 커버 화상의 연속 두 화소간의 차분 값과 양자화 범위를 이용하여 비밀 정보를 은닉시킨다. 특별히, 스테고 화상의 비가시성을 위해 커버 화상의 두 화소간의 차분 값에 따라 삽입 비트수를 다르게 한다. 또한, 기밀성을 위해서는 비밀 양자화 범위를 사용하여 제3자에 의해 비밀 정보가 해독되는 것을 방지할 수 있다. 제안 방식은 기존의 방식보다 화질을 개선시키기 위하여 범위의 상한값을 이용하였고, 삽입용량을 증가시키기 위해 특정 화소에 대해서는 삽입 처리를 중복으로 수행하였다 실험을 통하여 기존의 방식과 제안 방식을 비교하였고, 그 결과 제안 방식의 유효성을 확인할 수 있었다.

• 한국정보통신설비학회:학술대회논문집
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• 한국정보통신설비학회 2008년도 정보통신설비 학술대회
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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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• 제14권1호
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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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• 제8권3호
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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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• 제21권1호
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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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• 제10권2호
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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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• 제11권11호
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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.

• 한국멀티미디어학회논문지
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• 제7권7호
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• pp.913-921
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• 2004

데이터 은닉(data hiding)의 한 분야인 심층암호(steganography)는 제3자가 기밀정보의 삽입여부를 인지하지 못하도록 디지털화된 각종 미디어에 몰래 숨겨서 송/수신자간에 비밀통신을 할 수 있는 방법이다. 그러나 흑백으로만 구성되는 스캔된 텍스트 화상나 카툰 화상 등에 시각적으로 인지되지 않도록 기밀정보를 숨기는 것은 쉽지 않다. 본 논문에서는 이진 카툰 화상을 크기의 블록으로 분할한 후, 그 블록의 가운데 픽셀을 둘러싼 8-이웃 픽셀의 연속 길이를 이용하여 기밀 데이터를 숨기는 방식을 제안한다. 제안 방식은 어떤 조건에서는 가운데 픽셀에도 데이터를 은닉시켜 기밀정보의 삽입량을 증가시킬 수 있음을 보인다.

• 한국멀티미디어학회논문지
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• 제8권7호
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• pp.961-973
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• 2005

본 논문은 비트플레인 및 다중채널 특성을 이용한 컬러 영상의 적응 스테가노그라피 방법을 제안하였다. RGB 채널의 모든 비트플레인에 고정 임계값을 적용하여 정보를 삽입한 결과, 채널에 따른 화질 열화의 차이를 알 수 있었다. 따라서 본 연구에서는 BPCS (bit-plane complexity steganography) 방법의 고정 임계값 문제점을 해결하고 삽입용량과 화질을 개선하기 위하여 각 채널과 비트플레인 가중치를 정의하였다. 또한 비트플레인의 삽입 용량을 적응적으로 증가시키기 위하여, 커버 영상의 비트플레인 복잡도와 채널별 가중치를 이용하여 새로운 적응 임계값 설정 방법을 제안하였다. 실험에서는 컬러 영상에 동일한 화질과 동일한 정보량을 삽입하고, 이에 따른 삽입 용량과 채널별 화질을 비교하였다. 그 결과, 제안한 방법이 기존의 BPCS 방법보다 삽입 용량의 증가와 채널별 화질도 향상되었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권9호
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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.