• 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.

• 한국멀티미디어학회논문지
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• 제24권4호
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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.

• 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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• 제17권6호
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• pp.1674-1688
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• 2023

The remarkable advancement of quantum steganography offers enhanced security for quantum communications. However, there is a significant concern regarding the potential misuse of this technology. Moreover, the current research on identifying malicious quantum steganography is insufficient. To address this gap in steganalysis research, this paper proposes a specialized quantum steganalysis algorithm. This algorithm utilizes quantum machine learning techniques to detect steganography in general quantum secure communication schemes that are based on pure states. The algorithm presented in this paper consists of two main steps: data preprocessing and automatic discrimination. The data preprocessing step involves extracting and amplifying abnormal signals, followed by the automatic detection of suspicious quantum carriers through training on steganographic and non-steganographic data. The numerical results demonstrate that a larger disparity between the probability distributions of steganographic and non-steganographic data leads to a higher steganographic detection indicator, making the presence of steganography easier to detect. By selecting an appropriate threshold value, the steganography detection rate can exceed 90%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권5호
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• pp.2723-2740
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• 2017

Steganographic schemes which are based on minimizing an additive distortion function defined the overall impacts after embedding as the sum of embedding costs for individual image element. However, mutual impacts during embedding are often ignored. In this paper, an adaptive JPEG steganographic method based on weight distribution for embedding costs is proposed. The method takes mutual impacts during embedding in consideration. Firstly, an analysis is made about the factors that affect embedding fluctuations among JPEG coefficients. Then the Distortion Update Strategy (DUS) of updating the distortion costs is proposed, enabling to dynamically update the embedding costs group by group. At last, a kind of adaptive JPEG steganographic algorithm is designed combining with the update strategy and well-known additive distortion function. The experimental result illustrates that the proposed algorithm gains a superior performance in the fight against the current state-of-the-art steganalyzers with high-dimensional features.

• 융합신호처리학회논문지
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• 제20권4호
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• pp.205-211
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• 2019

스테그아날리시스(steganalysis)는 스테가노그래피(steganography)에 의해 숨겨진 데이터를 감지하고 복구하기 위한 기법이다. 스테그아날리시스 방법은 데이터 삽입 시 발생하는 시각적, 통계적 변화를 분석하여 숨겨진 데이터를 찾는다. 숨겨진 데이터를 복원하기 위해서는 어떤 스테가노그래피 방법에 의해 데이터가 숨겨졌는지를 알아야 한다. 그러므로 본 논문은 다층 분류를 통해 입력 영상에 적용된 스테가노그래피 방법을 식별하는 계층적 CNN 구조를 제안한다. 이를 위해 4개의 기본 CNN을 각각 입력 영상에 스테가노그래피 방법이 적용되었는지 여부나 서로 다른 두 스테가노그래피 방법 중에 어떤 방법이 적용되었는지를 이진 판별하도록 학습시켰으며, 학습된 CNN을 계층적으로 연결하였다. 실험 결과를 통해 제안된 계층적 CNN 구조는 4개의 서로 다른 스테가노그래피 방법인 LSB(Least Significant Bit Substitution), PVD(Pixel Value Difference), WOW(Wavelet Obtained Weights), UNIWARD(Universal Wavelet Relative Distortion)을 79%의 정확도로 식별할 수 있음을 확인하였다.

• 한국군사과학기술학회지
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• 제16권2호
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• pp.185-190
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• 2013

The previous steganographic methods by using the interpolation were difficult to estimate the distortion because the size of cover image is extended by interpolation algorithms. In this paper, to solve the problems of previous methods proposed the improved steganographic method based on the pixel replacement algorithms. In our method, we cannot extend a cover image, but also can estimate exactly the distortion of the stego-images. In the experimental results, the estimated distortion and embedding capacity of stego-image are shown on three pixel replacement methods.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 컴퓨터소사이어티 추계학술대회논문집
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• pp.157-160
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• 2003

Recently, several steganographic algorithms for two-color binary images have been proposed. In this paper, we propose a steganographic algorithm which embeds a secret message into bitmap images and palette-based images. To embed a message, the suggested algorithm divides a bitmap image into bit-plane images from LSB-plane to MSB-plane for each pixel, and considers each bit-plane image as a binary one. The algorithm splits each bit-plane image into m$\times$n blocks. and embeds a r-bit(r=[log$_2$(mn+1]-1) message into the block. And our schemes embed a message to every bit-plane from LSB to MSB to maximize the amount of embedded message and to minimize the degradation. The schemes change at most two pixels in each block. Therefore, the maximal color changes of the new algorithm are much smaller than other bit-plane embedding schemes' such as the substantial substitution schemes.

• IEIE Transactions on Smart Processing and Computing
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• 제5권4호
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• pp.250-255
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• 2016

Steganography is the art and science of secure communication. It focuses on both security and camouflage. Steganographic techniques must produce the resultant stego-image with less distortion and high resistance to steganalysis attack. This paper is mainly concerned with two steganographic techniques-least significant bit (LSB)++ and the reversible histogram transformation function (RHTF). LSB++ is likely to produce less distortion in the output image to avoid suspicion, but it is vulnerable to steganalysis attacks. RHTF using a mod function technique is capable of resisting the most popular and efficient steganalysis attacks, such as the regular-singular pair attack and chi-squared detection steganalysis, but it produces a lot of distortion in the output image. In this paper, we propose a new steganographic technique by combining both methods. The experimental results show that the proposed technique overcomes the respective drawbacks of each method.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 컴퓨터소사이어티 추계학술대회논문집
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• pp.23-26
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• 2003

Westfeld[1] analyzed a sequential LSB embedding steganography effectively through the $\chi$$^2$-statistical test which measures the frequencies of PoVs(pairs of values). Fridrich also proposed another statistical analysis, so-called RS steganalysis by which the embedding message rate can be estimated. In this paper, we propose a new steganographic scheme which preserves the above two statistics. The proposed scheme embeds the secret message in the innocent image by randomly adding one to real pixel value or subtracting one from it, then adjusts the statistical measures to equal those of the original image.