摘要
科技行业的快速发展带来信息量的暴增,各行各业都需要收集和应用大量的数据,海量数据在发挥价值的同时,给数据安全领域带来了史无前例的挑战。关系型数据库作为数据的底层存储载体之一,其存储的数据规模大、数据内容丰富、数据隐私度高。数据库的数据一旦泄露将会造成巨大的损失,保护数据库的所有权,确认数据的归属刻不容缓。对于现有的数据库水印技术来说,提高水印嵌入容量和减小数据失真之间存在固有矛盾问题,为了缓解此问题且进一步提高水印的鲁棒性,提出了一种基于动态差分扩展的强鲁棒数据库水印算法。该算法选取QR码作为水印,利用经过Haar小波变换的图像低频部分进行奇异值分解(SVD,singular value decomposition),提取部分特征值,用取余后的特征值作为待嵌入的水印序列,使得相同长度的水印序列包含更多信息,缩短了嵌入水印的长度。该算法结合自适应差分进化算法和最小差值算法选择最佳嵌入属性位,以缓解传统差分扩展技术在嵌入水印时计算效率低、数据失真大、鲁棒性差的问题,提高水印嵌入容量的同时减少了数据的失真。实验结果表明,该算法保证高水印嵌入率的同时数据失真较低,能够抵御多种攻击,具有良好的鲁棒性,追踪溯源的能力强,且与现有的算法对比优势明显,在数据安全领域具有广阔的应用前景。
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.
作者
汪天琦
张迎周
邸云龙
李鼎文
朱林林
WANG Tianqi;ZHANG Yingzhou;DI Yunlong;LI Dingwen;ZHU Linlin(Department of Computer Science,Nanjing University of Posts and Telecommunications,Nanjing 210023,China;Department of Software,Nanjing University of Posts and Telecommunications,Nanjing 210023,China;Department of Cyberspace Security,Nanjing University of Posts and Telecommunications,Nanjing 210023,China)
出处
《网络与信息安全学报》
2023年第5期150-165,共16页
Chinese Journal of Network and Information Security
关键词
数据库水印
差分进化
差分扩展
SVD
HAAR小波变换
QR码
database watermarking
differential evolution
difference expansion
singular value decomposition
Haar wavelet transform
quick response code
