Research on strong robustness watermarking algorithm based on dynamic difference expansion - Tianqi WANG; Yingzhou ZHANG; Yunlong DI; Dingwen LI; Linlin ZHU (网络与信息安全学报)
A surge in the amount of information comes with the rapid development of the technology industry.Across all industries, there is a need to collect and utilize vast amounts of data.While this big data holds immense value, it also poses unprecedented challenges to the field of data security.As relational databases serve as a fundamental storage medium for data, they often contain large-scale data rich in content and privacy.In the event of a data leak, significant losses may occur, highlighting the pressing need to safeguard database ownership and verify data ownership.However, existing database watermarking technologies face an inherent tradeoff between improving watermark embedding capacity and reducing data distortion.To address this issue and enhance watermark robustness, a novel robust database watermarking algorithm based on dynamic difference expansion was introduced.The QR code was employed as the watermark, the SVD decomposition of the low frequency part of the image was utilized after Haar wavelet transform.By extracting specific feature values and using residual feature values as the watermark sequence, it was ensured that the same-length watermark sequence contains more information and the embedded watermark length can be reduced.Furthermore, by combining the adaptive differential evolution algorithm and the minimum difference algorithm, the optimal embedding attribute bits were selected to alleviate the problems of low computational efficiency, high data distortion and poor robustness of traditional difference expansion techniques in embedding watermarks, and to improve the embedding capacity of watermarks while reducing the distortion of data.Experimental results demonstrate that the proposed algorithm achieves a high watermark embedding rate with low data distortion.It is resilient against multiple attacks, exhibiting excellent robustness and strong traceability.Compared to existing algorithms, it offers distinct advantages and holds great potential for broad application in the field of data security.