Detection of steganography in quantum grayscale images

Luo, Jia; Zhou, Ri-Gui; Hu, Wenwen; Luo, Gaofeng; Liu, Guangzhong

doi:10.1007/s11128-020-02649-x

Cited by 10 publications

(3 citation statements)

References 39 publications

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“…This protocol compares the difference in probability distribution of the quantum carrier before and after steganography. On the other hand, Luo et al [18] developed a quantum steganalysis algorithm specifically for the quantum multimedia steganography protocol based on the least significant bit.…”

Section: Quantum Steganalysismentioning

confidence: 99%

Special Quantum Steganalysis Algorithm for Quantum Secure Communications Based on Quantum Discriminator

2023

KSII TIIS

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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%.

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Section: Quantum Steganalysismentioning

confidence: 99%

Special Quantum Steganalysis Algorithm for Quantum Secure Communications Based on Quantum Discriminator

2023

KSII TIIS

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“…In classical image processing, the related processing algorithms mainly include image color processing, image geometric position processing, image morphology, image segmentation, object recognition, image recovery, image compression, image encryption, and so on. However, in the field of quantum image processing, there are too few corresponding image processing algorithms, so researchers need to do a lot of work [44][45][46][47][48][49][50][51][52][53][54][55][56].…”

Section: A Algorithm Researchmentioning

confidence: 99%

A New Trend of Quantum Image Representations

Guo

Liu

et al. 2020

IEEE Access

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Quantum image processing will be an important issue in the age of quantum computers. Quantum image processing generally includes quantum image representations, quantum image processing algorithms, and quantum image measurement. Among them, quantum image representation is a very important part of quantum image processing. Therefore, it is of great significance for quantum image processing to study the representation of quantum images. First, we elaborate on the main quantum image representations and analyze, compare and summarize them. This paper focuses on the definition of these quantum image representations the preparation of quantum images and the number of quantum bits required as well as the computational complexity. Then, this paper analyzes, compares and summarizes the similarities and differences between these quantum image representations. Finally, the challenges and future development in the field of quantum image processing are summarized and forecasted. This work will help researchers to understand the advances related to quantum image representations in the field of quantum image processing and is therefore of some reference value.

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“…尽管有许多的基于空域和变换域的量子图像信息隐藏算法问世, 但是现有的算法都是基于嵌入的方法, 会在载体图像上留下一定程度的修改痕迹而很难抵抗隐写分析方法的检测 [9] . 在经典受到了相关学者的关注, 其也在理论上显示出了与经典版本相比具有指数加速的潜力 [14] .…”

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Information Hiding Scheme Based on Quantum Generative Adversarial Network

Luo

Zhou

et al. 2021

J Comput-Aided Design Comput Graphics

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Due to the insecurity of quantum image information hiding technology in the face of statistical-based steganalysis algorithm detection, an information hiding scheme based on quantum generative adversarial network (QGAN) is proposed. This scheme first uses the mapping rules to map the secret information into the single qubit gate to prepare for the input state of the parameterized quantum circuit of the generator G . Then the stego quantum image is generated by the generating circuit in QGAN. Finally, the sample data obtained by measuring the stego image and the real data are used as the input of the discriminator D .The iterative optimization is performed so that G can obtain a stego image close to the target image. The experimental results show that proposed scheme can generate stego images that fit the target image distribution well and achieve the non-embedded hiding of information.

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Detection of steganography in quantum grayscale images

Cited by 10 publications

References 39 publications

Special Quantum Steganalysis Algorithm for Quantum Secure Communications Based on Quantum Discriminator

Special Quantum Steganalysis Algorithm for Quantum Secure Communications Based on Quantum Discriminator

A New Trend of Quantum Image Representations

Information Hiding Scheme Based on Quantum Generative Adversarial Network

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