• Journal of Broadcast Engineering
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• v.23 no.4
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• pp.462-473
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• 2018

Steganography is to hide information in a media data so naturally that the other users can not notice the existence of hidden information. Data encryption focuses on the complex encoding methods of information data in order to make it difficult to decode the information even though the other users notice the existence of information. On the other hand, steganography methods concentrate on natural hiding information into other media. Since the other users do not recognize the existence of hidden information, the information can be better protected. This paper introduces the concept of image steganography that an image information is concealed into another image (cover image), and proposes a new discrimination method of steganography. This paper explains the spatial methods with LSB manipulation and frequency methods using DCT coefficients. Finally, this paper proposes a new discrimination method of image steganography by inspecting that an image information is correctly decoded.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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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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• v.5 no.12
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• pp.2340-2354
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• 2011

A new and secure image steganographic scheme based on nonuniform discrete Fourier transform (NDFT) is proposed in this paper. First, the chaotic system is introduced to select embedding points randomly in NDFT domain suitable range, and NDFT is implemented on every non-overlapping block of eight consecutive pixels. Second, the secret messages are scrambled by chaotic systems, and embedded into frequency coefficients by quantization method. The stego-image is obtained by inverse NDFT (INDFT). Besides, in order to discriminate tampers, the low frequency wavelet coefficients of 7 most significant bits (MSBs) of the stego-image are converted into the binary sequence after nonuniform scalar quantization. Then the obtained binary sequence is scrambled by the chaotic systems, and embedded into the least significant bit (LSB) of the stego-image. Finally, the watermarked stego-image can be obtained by a new improved LSB steganographic method. The embedded secret messages can be extracted from the watermarked stego-image without the original cover image. Experimental results show the validity of the proposed scheme, and dual statistics attacks are also conducted to indicate the security.