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CRC Press eBooks

Quantum Video Steganography

Zhiheng Zhao, Xianhua Song, Ahmed A. Abd El‐Latif, Basma Abd El-Rahiem

Published May 15, 2026• 0 citations
Publisher

Abstract

Quantum video information steganography holds significant research value in the era of quantum computing. Compared to image-based media, videos possess greater storage capacity and redundant information, making them more suitable as carriers for secret information. This chapter introduces a least significant qubit (LSQb) steganography algorithm for quantum videos in the Quantum Video based on Novel Enhanced Quantum Representation (QVNEQR) representation. Based on LSQb and the motion vectors of quantum videos, a quantum video motion vector steganography method is proposed. This algorithm embeds secret information into the motion vectors of quantum videos using the LSQb algorithm, encoding the secret information into the quantum bitstreams of the motion vectors. This approach enhances the security of quantum video steganography.

DOI
10.1201/9781003621423-8

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CRC Press eBooks•May 15, 2026•0 citations
Quantum video information steganography holds significant research value in the era of quantum computing. Compared to image-based media, videos possess greater storage capacity and redundant information, making them more suitable as carriers for secret information. This chapter introduces a least significant qubit (LSQb) steganography algorithm for quantum videos in the Quantum Video based on Novel Enhanced Quantum Representation (QVNEQR) representation. Based on LSQb and the motion vectors of quantum videos, a quantum video motion vector steganography method is proposed. This algorithm embeds secret information into the motion vectors of quantum videos using the LSQb algorithm, encoding the secret information into the quantum bitstreams of the motion vectors. This approach enhances the security of quantum video steganography.
Quantum information hiding will have important researching value in quantum computer era. It is more appropriate for videos to be carriers for information hiding than images because of its bigger information content. A novel quantum video information hiding algorithm is proposed based on improved LSQb and motion vector of quantum video. Based on quantum color video representation QVNEQR, the improved LSQb information hiding algorithm is implemented on the original quantum video domain. Then, the improved LSQb is selected to embed the secret information into the motion vector to make the steganography more secure. Experimental simulations conducted on a simple video demonstrate the efficiency of the proposed approach.
As one of important research branches of quantum information hiding, quantum steganography embeds secret information into quantum images for covert communication by integrating quantum secure communication technology and classical steganography. In this paper, based on the novel enhanced quantum representation (NEQR), a novel quantum steganography algorithm is proposed to transfer secret information by virtue of quantum watermarked image. In order to achieve this goal, the least significant qubit (LSQb) of quantum carrier image is replaced with the secret information by implementing quantum circuit. Compared with the previous quantum steganography algorithms, the communicating parties can recover the secret information tampered, meanwhile the tampers can be located effectively. In the experiment result, the peak signal-to-noise ratios (PSNRs) are calculated for different quantum watermarked images and quantum watermarks, which demonstrate the imperceptibility of the algorithm is good and the secret information embedded can be recovered by virtue of its self-adaptive mechanism.
Embedding secret information into quantum carrier image for covert communication is one of significant research fields of quantum secure communication. Using good imperceptibility and high embedding efficiency of matrix coding, this paper proposes a novel matrix coding-based quantum steganography algorithm for quantum color images. In order to better apply matrix coding in actual demand, two different embedding methods are proposed. One embedding method is single pixel-embedded (1, 3, 2) coding, called SPE (1, 3, 2) coding for short. This method embeds two qubits of secret information into three least significant qubits (LSQbs) of a single pixel of quantum carrier image, and at most only one LSQb would be changed. The other embedding method is the multiple pixels-embedded (1, 3, 2) coding, called MPsE (1, 3, 2) coding, in which three LSQbs of multiple carrier pixels are utilized to embed two secret qubits. On account of experimental simulation obtained in the MATLAB environment, it shows that the new algorithm has good performance in the imperceptibility, the security, the embedding efficiency, and the embedding capacity.
Currently, quantum steganography schemes utilizing the least significant bit (LSB) approach are primarily optimized for fixed-point data processing, yet they encounter precision limitations when handling extended floating-point data structures owing to quantization error accumulation. To overcome precision constraints in quantum data hiding, the EPlsb-MFQS and MVlsb-MFQS quantum steganography algorithms are constructed based on the LSB approach in this study. The multichannel floating-point quantum representation of digital signals (MFQS) model enhances information hiding by augmenting the number of available channels, thereby increasing the embedding capacity of the LSB approach. Firstly, we analyze the limitations of fixed-point signals steganography schemes and propose the conventional quantum steganography scheme based on the LSB approach for the MFQS model, achieving enhanced embedding capacity. Moreover, the enhanced embedding efficiency of the EPlsb-MFQS algorithm primarily stems from the superposition probability adjustment of the LSB approach. Then, to prevent an unauthorized person easily extracting secret messages, we utilize channel qubits and position qubits as novel carriers during quantum message encoding. The secret message is encoded into the signal’s qubits of the transmission using a particular modulo value rather than through sequential embedding, thereby enhancing the security and reducing the time complexity in the MVlsb-MFQS algorithm. However, this algorithm in the spatial domain has low robustness and security. Therefore, an improved method of transferring the steganographic process to the quantum Fourier transformed domain to further enhance security is also proposed. This scheme establishes the essential building blocks for quantum signal processing, paving the way for advanced quantum algorithms. Compared with available quantum steganography schemes, the proposed steganography schemes achieve significant improvements in embedding efficiency and security. Finally, we theoretically delineate, in detail, the quantum circuit design and operation process.