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Secure and High-Quality Watermarking Algorithms for Relational Database Based on Semantic

Authors :
Li, Wenling
Li, Ning
Yan, Jianen
Zhang, Zhaoxin
Yu, Ping
Long, Gang
Source :
IEEE Transactions on Knowledge and Data Engineering; 2023, Vol. 35 Issue: 7 p7440-7456, 17p
Publication Year :
2023

Abstract

Relational databases are widely applied in various industries, such as government departments, medical institutions and enterprises, for data storage and relationship management. It is convenience to data maintenance, however, the data in it maybe vulnerable to be forged or tampered with. Therefore, protecting the copyright of relational databases is a critical issue. Fortunately, watermarking technology can be used to prove copyright ownership. Since the digital watermarking technology can solve this problem effectively, based on semantic, we propose two watermarking approaches with high security and strong robustness for numeric and non-numeric data of relational databases in this paper. On the one hand, we propose a reversible numeric watermarking approach. It performs the replacement operation at the semantic level and retain the statistical characteristics of the data. On the other hand, based on word segmentation and word embedding, the non-numerical attributes of the relational database with natural language are chosen to embed watermark. It is noteworthy that the proposed mechanism can be applied to both Chinese and English with minimum distortion. Additionally, we also propose the virtual splitting of attribute column and the principle of modification minimum to guarantee the capacity of watermark and reduce the data modification rate. Additionally, the BCH (31,16,7) error control code is added to the binary watermark string to improve the detection rate of watermark. Based on the above innovations, the security of watermarking algorithm is improved successfully by double encryption (chaos encryption and hash encryption) with two keys (the user's private key and the attribute column key). The simulation results demonstrate that the proposed two algorithms in this paper have stronger robustness on defensing malicious attacks than previous works.

Details

Language :
English
ISSN :
10414347 and 15582191
Volume :
35
Issue :
7
Database :
Supplemental Index
Journal :
IEEE Transactions on Knowledge and Data Engineering
Publication Type :
Periodical
Accession number :
ejs63270249
Full Text :
https://doi.org/10.1109/TKDE.2022.3194191