Robust Audio Watermarking Against the D/A and A/D conversions (0707.0397v1)

Abstract: Audio watermarking has played an important role in multimedia security. In many applications using audio watermarking, D/A and A/D conversions (denoted by DA/AD in this paper) are often involved. In previous works, however, the robustness issue of audio watermarking against the DA/AD conversions has not drawn sufficient attention yet. In our extensive investigation, it has been found that the degradation of a watermarked audio signal caused by the DA/AD conversions manifests itself mainly in terms of wave magnitude distortion and linear temporal scaling, making the watermark extraction failed. Accordingly, a DWT-based audio watermarking algorithm robust against the DA/AD conversions is proposed in this paper. To resist the magnitude distortion, the relative energy relationships among different groups of the DWT coefficients in the low-frequency sub-band are utilized in watermark embedding by adaptively controlling the embedding strength. Furthermore, the resynchronization is designed to cope with the linear temporal scaling. The time-frequency localization characteristics of DWT are exploited to save the computational load in the resynchronization. Consequently, the proposed audio watermarking algorithm is robust against the DA/AD conversions, other common audio processing manipulations, and the attacks in StirMark Benchmark for Audio, which has been verified by experiments.

• The paper introduces a novel DWT-based watermarking algorithm that combats wave magnitude distortion and linear temporal scaling caused by DA/AD conversions.
• The paper validates its approach with metrics like BER, SNR, and ODG, demonstrating superior robustness compared to existing methods.
• The paper employs adaptive embedding and synchronization codes for resynchronization, laying the groundwork for practical audio watermarking in analog systems.

Robust Audio Watermarking Against DA/AD Conversions

This paper presents a robust audio watermarking algorithm designed to tackle the specific challenges posed by Digital-to-Analog (DA) and Analog-to-Digital (AD) conversions. Despite the critical role of audio watermarking in multimedia security and ownership protection, previous research has largely overlooked the impact of DA/AD conversions on watermark robustness. This paper identifies the primary challenges as wave magnitude distortion and linear temporal scaling, both of which can significantly degrade the watermarked audio signal and impede successful watermark extraction.

The authors propose a novel DWT-based (Discrete Wavelet Transform) audio watermarking algorithm to enhance resistance to DA/AD conversions. The algorithm employs two key strategies: first, it combats wave magnitude distortion by leveraging the relative energy relationships among different groups of DWT coefficients in the low-frequency sub-band, thereby adaptively controlling the embedding strength. Second, it addresses linear temporal scaling through a resynchronization mechanism using synchronization codes. The time-frequency localization characteristics of DWT help minimize computational load during resynchronization, increasing efficiency.

Experimental results demonstrate the algorithm’s robustness against DA/AD conversions and other common audio manipulations. The proposed watermarking strategy also shows defiance against signal processing manipulations and attacks as outlined by the StirMark Benchmark for Audio. Moreover, the paper contrasts the new approach against several existing methods with analyses indicating improved performance in resisting audio degradation through DA/AD conversions.

Key Numerical Results and Methodological Insights

• Degradation Analysis: The DA/AD conversions result in linear temporal scaling and wave magnitude distortion, which the algorithm effectively mitigates. Authors model these distortions mathematically and suggest parameter values for practical implementations.
• DWT-based Embedding: Utilizing DWT, the embedding strategy is architecture-specific to achieve robustness against signal distortions. Relative energy relationships between coefficients are used to bolster defenses against magnitude distortion.
• Synchronization and Resynchronization: The algorithm’s robustness is partly owed to synchronization codes that efficiently manage shifts in audio samples, essential for counteracting the linear time-scaling effects. Lagrange linear interpolation techniques further economize on computational resources during resynchronization.
• Error Analysis: The paper presents detailed evaluation metrics such as BER, SNR, and ODG to assess audio quality and robustness. It meticulously calculates the likelihood of synchronization errors and implements ECC-based local redundancy to enhance correction.
• Data Capacity: With an approximate data embedding capacity of 28.71 bps, the system offers practical application potential, capturing a balance between robustness, data payload, and audio quality.

Implications and Future Directions

The authors contribute a significant method to enhance audio watermarking resilience against unavoidable DA/AD processes, a scenario often encountered in real-world audio distribution systems. The research verifies that methods like DWT and strategic embedding of relative energy values in the frequency domain can effectively shield the watermark against extensive DA/AD related distortions. This work potentially paves the way for deploying robust watermarking procedures in analog environments, thus broadening the operational horizon of secure audio technologies.

For future work, exploring the behavior of this watermarking approach across different analog channels and DA/AD conversion devices would be beneficial. Analyzing a wider variety of soundcard performances and extending synchronization strategies could further refine robustness and practical viability. Moreover, integrating more advanced error correction codes might enhance the scheme’s resilience and data integrity preservation in even more challenging audio processing environments.