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Chinese Control Conference (CCC)

A Quantum Audio Watermarking Scheme

Kehan Chen, Fei Yan, Abdullah M. Iliyasu, Jianping Zhao

Published Jul 1, 2018• 4 citations
Publisher

Abstract

The study presented in this work explores the implementation of a watermarking scheme for quantum audio signals based on quantum Discrete Cosine Transformation (qDCT). The qDCT transforms the quantum host audio signal which is encoded as an FRQA (flexible representation of quantum audio) content from time domain to frequency domain and manipulates or modifies the high-frequency positions to embed the quantum watermark audio information into it. The strong energy compaction property of DCT is utilized in this scheme, i.e. after the DCT process to a digital audio, most of the signal information tends to be concentrated in a few low-frequency components and its high-frequency components could record some extra information like watermark audio. Built on the circuit model of quantum computation, the circuit networks to execute the embedding and extraction procedures of qDCT-based watermarking algorithm are designed and simulation-based experiments are conducted to demonstrate their implementation.

DOI
10.23919/chicc.2018.8483507

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The study presented in this work explores the implementation of a watermarking scheme for quantum audio signals based on quantum Discrete Cosine Transformation (qDCT). The qDCT transforms the quantum host audio signal which is encoded as an FRQA (flexible representation of quantum audio) content from time domain to frequency domain and manipulates or modifies the high-frequency positions to embed the quantum watermark audio information into it. The strong energy compaction property of DCT is utilized in this scheme, i.e. after the DCT process to a digital audio, most of the signal information tends to be concentrated in a few low-frequency components and its high-frequency components could record some extra information like watermark audio. Built on the circuit model of quantum computation, the circuit networks to execute the embedding and extraction procedures of qDCT-based watermarking algorithm are designed and simulation-based experiments are conducted to demonstrate their implementation.
Abstract. This paper presents an energy-aware quantum audio watermarking framework that exploits quantum signal transformations and clustering techniques to achieve robust and imperceptible watermark embedding. The proposed method integrates the Quantum Discrete Wavelet Transform (QDWT), Quantum Discrete Cosine Transform (QDCT), quantum k-means (Q-means) clustering, and a dynamic XOR-based embedding mechanism. The host audio signal is segmented into frames and analyzed in the quantum transform domain to extract joint time–frequency features. Based on the transform-domain energy characteristics and clustering outcomes, perceptually tolerant embedding regions are adaptively identified using predefined energy thresholds. Watermark insertion is performed through quantum-controlled XOR operations, where the embedding depth is dynamically selected according to the energy level of each audio segment. This energy-driven strategy ensures minimal perceptual distortion while enhancing robustness against signal processing attacks. Experimental evaluations demonstrate that the proposed method consistently outperforms conventional LSB-based watermarking schemes, achieving high transparency with signal-to-noise ratio (SNR) values exceeding 60 dB and strong robustness with bit error rates (BER) below 0.1 under various qubit-flip noise and zero-attack scenarios. These results confirm the effectiveness of the proposed framework in preserving audio quality while maintaining reliable watermark recovery.
As one of essential multimedia in quantum networks, the copyright protection of quantum audio has gradually become an important issue in the domain of quantum information hiding in the decades. In this paper, an improved quantum watermarking algorithm based on quantum audio by using least significant qubit (LSQb) modification is proposed. Compared with the previous achievements, it can effectively improve the robustness and security of watermark for copyright protection of quantum audio. In the new algorithm, the least significant bites and the peripheral least significant bits of the amplitudes are modified in terms of their logical consistency and correlation to enhance watermark robustness of resisting various illegal attacks. Furthermore, the new algorithm can avoid the weak robustness defect of many previous algorithms that directly embedded the watermark into the least significant bits. In order to implement the new algorithm, some specific quantum circuits are designed to obtain better applicability and scalability for embedding and extracting watermark. Finally, the simulation results including the values of audio waveforms and signal to noise ratios (SNR) prove that the new algorithm has good transparency, robustness, and security.
A novel watermarking scheme for quantum image is proposed based on Quantum cosine transform (QCT). The cosine coefficients are extracted by executing QCT on quantum image. A dynamic vector for controlling embedding strength instead of a fixed parameter for embedding process in other scheme is utilized to process quantum watermark. The adder operation and the inverse QCT are implemented which offset the QCT and guarantee the embedding process having smaller impact on the quantum carrier image. Simulation results and analysis show that the proposed dynamic watermarking scheme has better visual quality under a higher embedding capacity.
Abstract The crazy, unconscious use of the Internet, and the increase in cybercrime and hacking, which resulted in the loss of a large number of sensitive data, the risk of piracy, etc. were the motivation for protecting rights, securing and hiding essential information such as images, audio, etc. Watermarking was a popular security, copyright and privacy approach and one of the problems in modern quantum digital computing that produced more powerful quantum protection techniques than the classical one that used classical techniques such as digital wavelet transformation and Hungarian algorithms. Recent advances in quantum image representation and processing help to manipulate data hidden. This paper proposes a new watermark technique in which a color watermark image is hidden within another color-carrying image after transformation into the quantum domain using the recently completed quantum color image representation technique. Finally, a comparison is made between the proposed method and the most recent watermarking techniques is establish in terms of PSNR (peak signal-to-noise ratio), which shows the high precision of the proposed technique and improves the imperceptibility compared to the related schemes.
The Discrete Cosine Transform (DCT) is an integral part of classical image compression, which becomes the basis of the JPEG standard. With advances in quantum computing, there is growing interest in exploring quantum analogues of classical algorithms for such transforms. This paper presents a simulation of the Quantum Discrete Cosine Transform (QDCT) using the Qiskit Python library, applied to standard grayscale images segmented into 8x8 and 4x4 blocks. The QDCT algorithm is formulated as a unitary operator and evaluated using state-vector simulation. Due to the current constraints of quantum hardware and challenges in circuit synthesis, this study focused on simulation results, as direct quantum circuit measurement leads to amplitude collapse and unusable output. The performance of QDCT is quantitative compared to classical DCT using Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and compression ratio metrics. The result of this study reveals the feasibility and current limitations of QDCT-based image compression while providing a reproducible benchmark for future quantum image processing research. This study offers a realistic assessment of the potential and technical limitations of QDCT in the context of emerging quantum technologies.
With the ubiquity and primacy of image- and video-processing, a new subdiscipline ensuring a smooth transition from digital to quantum image-processing has emerged. This study proposes a framework to synchronize audio and visual content to realize talking quantum movies. This framework segments a movie into frame, audio, and time components. A multichannel representation for quantum images (MCQI) is used to encode the still images that make up movie frames. In addition, the amplitude content of the flexible representation of the quantum audio (FRQA) signal is recorded at each instant of time. The synchronization of audio and frames in the movie is accomplished through a quantum sequence of time. The feasibility of this framework is demonstrated by a simple simulation, and some possible applications are discussed.