• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.382-403
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• 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)
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• v.18 no.1
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• pp.170-191
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• 2024

The transmission of confidential data using cover media is called steganography. The three requirements of any effective steganography system are high embedding capacity, security, and imperceptibility. The text file's structure, which makes syntax and grammar more visually obvious than in other media, contributes to its poor imperceptibility. Text steganography is regarded as the most challenging carrier to hide secret data because of its insufficient redundant data compared to other digital objects. Unicode characters, especially non-printing or invisible, are employed for hiding data by mapping a specific amount of secret data bits in each character and inserting the character into cover text spaces. These characters are known with limited spaces to embed secret data. Current studies that used Unicode characters in text steganography focused on increasing the data hiding capacity with insufficient redundant data in a text file. A sequential embedding pattern is often selected and included in all available positions in the cover text. This embedding pattern negatively affects the text steganography system's imperceptibility and security. Thus, this study attempts to solve these limitations using the Part-of-speech (POS) tagging technique combined with the randomization concept in data hiding. Combining these two techniques allows inserting the Unicode characters in randomized patterns with specific positions in the cover text to increase data hiding capacity with minimum effects on imperceptibility and security. Format-preserving encryption (FPE) is also used to encrypt a secret message without changing its size before the embedding processes. By comparing the proposed technique to already existing ones, the results demonstrate that it fulfils the cover file's capacity, imperceptibility, and security requirements.

• 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.

• Journal of Broadcast Engineering
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• v.22 no.5
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• pp.643-651
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• 2017

Steganography is one of information hiding technologies and discriminated from cryptography in that it focuses on avoiding the existence the hidden information from being detected by third parties, rather than protecting it from being decoded. In this paper, as an image steganography method which uses images as media, we propose a new block matching method that embeds information into the discrete wavelet transform (DWT) domain. The proposed method, based on a statistical analysis, reduces loss of embedding capacity due to inequable use of candidate blocks. It works in such a way that computes the variance of each candidate block, preserves candidate blocks with high frequency components while reducing candidate blocks with low frequency components by compressing them exploiting the k-means clustering algorithm. Compared with the previous block matching method, the proposed method can reconstruct secret images with similar PSNRs while embedding higher-capacity information.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.427-442
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• 2022

MP3 is one of the most widely used file formats for encoding and representing audio data. One of the reasons for this popularity is their significant ability to reduce audio file sizes in comparison to other encoding techniques. Additionally, other reasons also include ease of implementation, its availability and good technical support. Steganography is the art of shielding the communication between two parties from the eyes of attackers. In steganography, a secret message in the form of a copyright mark, concealed communication, or serial number can be embedded in an innocuous file (e.g., computer code, video film, or audio recording), making it impossible for the wrong party to access the hidden message during the exchange of data. This paper describes a new steganography algorithm for encoding secret messages in MP3 audio files using an improved least significant bit (LSB) technique with high embedding capacity. Test results obtained shows that the efficiency of this technique is higher compared to other LSB techniques.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.395-402
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• 2004

In this paper, we proposed a new method of the large capacity steganography using adaptive threshold on bit planes. Applying fixing threshold, if we insert information into all bit planes, all bit planes showed different image quality. Therefore, we first defined the bit plane weight to solve the fixing threshold problem. We then proposed a new adaptive threshold method using the bit plane weight and the average complexity to increase insertion capacity adaptively. In the experiment, we inserted information into the standard images with the same image quality and same insertion capacity, and we analyzed the insertion capacity and image duality. As a result, the proposed method increased the insertion capacity of about 6% and improved the image quality of about 24dB than fixed threshold method.

• ETRI Journal
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• v.43 no.3
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• pp.561-570
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• 2021

This paper presents master key identifier based protocol steganography (MKIPS), a new approach toward creating a covert channel within the Secure Real-time Transfer Protocol, also known as SRTP. This can be achieved using the ability of the sender of Voice-over-Internet Protocol packets to select a master key from a pre-shared list of available cryptographic keys. This list is handed to the SRTP sender and receiver by an external key management protocol during session initiation. In this work, by intelligent utilization of the master key identifier field in the SRTP packet creation process, a covert channel is created. The proposed covert channel can reach a relatively high transfer rate, and its capacity may vary based on the underlying SRTP channel properties. In comparison to existing data embedding methods in SRTP, MKIPS can convey a secret message without adding to the traffic overhead of the channel and packet loss in the destination. Additionally, the proposed covert channel is as robust as its underlying user datagram protocol channel.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4788-4813
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• 2019

In this paper, we introduce concepts of optimal and near optimal secret data hiding schemes. We present a new digital image steganography approach based on the Galois field $GF(p^m)$ using graph and automata to design the data hiding scheme of the general form ($k,N,{\lfloor}{\log}_2p^{mn}{\rfloor}$) for binary, gray and palette images with the given assumptions, where k, m, n, N are positive integers and p is prime, show the sufficient conditions for the existence and prove the existence of some optimal and near optimal secret data hiding schemes. These results are derived from the concept of the maximal secret data ratio of embedded bits, the module approach and the fastest optimal parity assignment method proposed by Huy et al. in 2011 and 2013. An application of the schemes to the process of hiding a finite sequence of secret data in an image is also considered. Security analyses and experimental results confirm that our approach can create steganographic schemes which achieve high efficiency in embedding capacity, visual quality, speed as well as security, which are key properties of steganography.

• 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.