Abstract
In 2002, Agrawal and Kiernan defined six basic requirements, including preventing illegal watermark embedding and authentication, reversibility, robustness, and others, which must be satisfied when a reversible watermark is designed for relational databases. To meet these requirements, in this paper, a lossless watermarking scheme for a categorical relational database called LRW-CRDB (lossless robust watermarking for categorical relational databases) is proposed. In our LRW-CRDB scheme, the database owner needs to generate two secret embedding keys, K1 and K2, in advance. Then, two reference sets are generated based on two different secret embedding keys and a symmetry-based data hiding strategy, and then these are used for the watermark embedding phases. Experimental results confirmed that our LRW-CRDB scheme successfully detects 100% of hidden watermarks, even when more than 95% of the watermarked relational database has been deleted. In other words, the robustness of our proposed LRW-CRDB scheme outperforms other existing schemes under a variety of possible attacks, such as alteration, sorting, deletion, and mix-match attacks.
Highlights
With the rapid development of the Internet and digital processing technologies, the ownership protection of digital content, such as an image, audio, videos, and so on, has become a crucial issue
The second type is the fragile watermarking technique [6,7,8], in which the hidden watermark will be affected by various operations, no matter if they are conducted by malicious attackers or innocent users
We discuss the robustness analysis of our watermarking scheme with different parameters
Summary
With the rapid development of the Internet and digital processing technologies, the ownership protection of digital content, such as an image, audio, videos, and so on, has become a crucial issue. Odeh [18] proposed a new database watermarking scheme that based on inserting a binary image watermark into the non-numeric multi-word attributes of selected tuples Their scheme is a blind technique, which means that their scheme does not need the original database for extracting the hidden watermark. Further enhance the robustness when the database contains more than 10% destroyed content, in 2012, Farfoura et al [22] proposed a blind, reversible, watermarking scheme based on a reversible data hiding technique called ‘prediction-error expansion’ on integers Their scheme was designed only for numerical attributes, but it successfully detects the watermarked data with 100% accuracy, even when more than 60% of the content of the watermarked relational database has been modified.
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