• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권7호
• /
• pp.3778-3793
• /
• 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.

• 한국컴퓨터정보학회:학술대회논문집
• /
• 한국컴퓨터정보학회 2019년도 제59차 동계학술대회논문집 27권1호
• /
• pp.111-114
• /
• 2019

최근 봇넷(Botnet)은 PC 뿐만 아니라 IoT 기기를 대상으로 확대되어 구축되고 있으며, 최신 기술들이 적용되면서 탐지와 방어가 어렵도록 구축되고 있다. 특히, 해커와 테러범 사이에서 많이 활용되는 정보 은닉 기술인 스테가노그래피(Steganography)가 적용된 Botnet(Stego-botnet)이 출현하였는데, 기존의 Botnet 형태와는 달리 SNS 환경을 Botnet 개체 사이의 통신 기반으로 활용하며 Steganography 기술로 통신 내용을 숨겨 탐지가 어렵기 때문에 그 위험성과 피해가 심각할 수 있다. 본 논문에서는 SNS 환경에서의 Steganography 기반 Botnet 구축 가능성을 조사하고, 실제로 카카오톡을 활용한 Steganography 기반 Botnet 통신 가능성을 실험한 후 결과를 제시하며, Steganography 기반 Botnet에 대한 탐지 및 역추적 방안을 간략히 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제14권3호
• /
• pp.1228-1248
• /
• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제14권1호
• /
• pp.382-403
• /
• 2020

Steganography is the art of concealing the existence of a secret data in a non-secret digital carrier called cover media. While the image of steganography methods is extensively researched, studies on other cover files remain limited. Videos are promising research items for steganography primitives. This study presents an improved approach to video steganography. The improvement is achieved by allowing senders and receivers exchanging secret data without embedding the hidden data in the cover file as in traditional steganography methods. The method is based mainly on searching for exact matches between the secret text and the video frames RGB channel pixel values. Accordingly, a random key-dependent data is generated, and Elliptic Curve Public Key Cryptography is used. The proposed method has an unlimited embedding capacity. The results show that the improved method is secure against traditional steganography attacks since the cover file has no embedded data. Compared to other existing Steganography video systems, the proposed system shows that the method proposed is unlimited in its embedding capacity, system invisibility, and robustness. The system achieves high precision for data recovery in the receiver. The performance of the proposed method is found to be acceptable across different sizes of video files.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제9권12호
• /
• pp.5209-5228
• /
• 2015

According to the characteristics of adaptive JPEG steganography which determines the changed DCT coefficients based on embedding distortion, a new steganalysis method by selecting the DCT coefficients with small distortion values is proposed. Firstly, the principle of adaptive JPEG steganography through minimizing distortion is introduced. Secondly, the practicability of selecting the changed DCT coefficients according to distortion values is studied. Thirdly, the proposed steganalysis method is given and the embedding sensitivity of the steganalysis feature extracted from the selected DCT coefficients is analyzed. Lastly, the implement processes of the proposed method are presented and analyzed in details. In the experiments, PQt, PQe and J-UNIWARD steganography are used as examples to verify the effect of the proposed steganalysis method for adaptive JPEG steganography. A serial experimental results show the detection accuracy can be improved obviously, especially when the payload is relatively low.

• 한국산업정보학회논문지
• /
• 제19권5호
• /
• pp.51-56
• /
• 2014

인터넷의 디지털 세상에서 스테가노그래피는 의심스럽지 않은 커버 매체 안에 비밀 메시지를 숨겨서 비밀 통신의 존재를 은닉하기 위해 도입되었다. 제 3자는 비밀 메시지가 전달되는 사실을 인식하지 못한다. 텍스트 기반 스테가노그래피 기법은 다양하게 적용할 수 있다. 이 논문에서는 존재하는 각각의 텍스트 스테가노그래픽 기법의 장점과 단점을 분석하고, 효율적인 접근 방법을 제시한다. 외부적 공격으로부터 비밀 메시지를 안전하게 숨기기 위해 재배열 순서키에 의한 방법을 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권4호
• /
• pp.1553-1567
• /
• 2021

Steganography is a current hot research topic in the area of information security and privacy protection. However, most previous steganography methods are not effective against steganalysis and attacks because they are usually carried out by modifying covers. In this paper, we propose an improved coverless text steganography algorithm based on pretreatment and Part of Speech (POS), in which, Chinese character components are used as the locating marks, then the POS is used to hide the number of keywords, the retrieval of stego-texts is optimized by pretreatment finally. The experiment is verified that our algorithm performs well in terms of embedding capacity, the embedding success rate, and extracting accuracy, with appropriate lengths of locating marks and the large scale of the text database.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제16권3호
• /
• pp.986-1005
• /
• 2022

Text steganography is one of the most imminent and promising research interests in the information security field. With the unprecedented success of the neural network and natural language processing (NLP), the last years have seen a surge of research on generative linguistic steganography (GLS). This paper provides a thorough and comprehensive review to summarize the existing key contributions, and creates a novel taxonomy for GLS according to NLP techniques and steganographic encoding algorithm, then summarizes the characteristics of generative linguistic steganographic methods properly to analyze the relationship and difference between each type of them. Meanwhile, this paper also comprehensively introduces and analyzes several evaluation metrics to evaluate the performance of GLS from diverse perspective. Finally, this paper concludes the future research work, which is more conducive to the follow-up research and innovation of researchers.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제17권1호
• /
• pp.120-144
• /
• 2023

With the expansion of digital communication networks, a considerable number of randomization techniques have been invented and implemented to enhance the different data transmission algorithms' levels of security. Steganography is among the data transmissions techniques used to hide secret data. Nowadays, several randomization techniques have been used in steganography to elevate the security of transmitted data. Unfortunately, the majority of these techniques lack some simplicity, efficiency, and flexibility, in addition to other limitations. This research presents a new randomization technique called Rand-Stego. Rand-Stego could be applied/practiced over any steganography technique. It provides simplicity and efficiency and elevates the security level. Examples of implementing the proposed technique on some steganography algorithms will be explored. The proposed and current techniques will be compared. The obtained results show Rand-Stego's superiority in terms of efficiency and flexibility when compared to the current techniques.

• 스마트미디어저널
• /
• 제12권4호
• /
• pp.9-18
• /
• 2023

스테가노그래피는 데이터의 존재 자체를 은닉하여 데이터를 보호하는 기술이다. 최근에는 인공지능 기술이 발달함에 따라 딥러닝 기반의 스테가노그래피 기법들이 개발되고 있다. 딥러닝 기술은 데이터에 대한 고차원의 특징을 분석하여 학습할 수 있으므로 스테가노그래피의 성능과 품질을 개선시킬 수 있다. 본 논문에서는 이미지데이터에 대한 딥러닝 기반의 스테가노그래피 기술의 최신 연구 동향에 대해 살펴보도록 한다.