الفهرس 
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Abstract
Digital multimedia watermarking technology was suggested in the last decade to embed copyright information in digital objects such as images, audio and video. However, the increasing use of relational database systems in many real-life applications created an ever increasing need for watermarking database systems. As a result, watermarking relational database systems are now merging as a research area that deals with the legal issue of copyright protection and tamper detection of database systems.
Watermarking of relational database system is a relatively new field and thus research literature has been very limited and reported results are insufficient. Most of these proposed researches are irreversible watermarking. Accordingly, this thesis propose reversible watermarking algorithms, which is also called invertible watermark, or erasable watermark, helps to recover back the original data after the content has been authenticated. Such reversibility is highly desired in some sensitive database applications, e.g. in military and medical data. Permanent distortion is one of the main drawbacks of the entire irreversible relational database watermarking schemes.
There are two basic types of watermarking techniques, these are, robust and fragile watermarking. The first type of watermarking is robustness, which enables the watermarked data to resist a variety of malicious attacks and benign modifications of the user. The second type of watermarking is that a fragile watermark for tamper detection is used to identify and report every possible region in which someone has tampered with the watermarked data.
This work, presents two effective and blinded watermarking schemes for relational database to process the robust and fragile watermark using multilevel histogram modification algorithm. In the first scheme, a new reversible fragile watermarking algorithm is presented. Fragile watermarking is commonly used for content authentication and tamper detection in relational database. In the proposed scheme more peak points are used for hiding secret bits. So, the hiding capacity is enhanced compared with those conventional methods based on one or two level histogram modification. Furthermore, the proposed algorithm detects, localizes and characterizes malicious alterations made to relational database at group level using multilevel histogram modification method that modifies the difference histogram and characteristics of numeric data values. All tuples are first securely divided into groups, and then apply histogram modification watermarks to each group independently and evaluate the local characteristics of database relation like frequency distribution of bits. A sequential recovery strategy is exploited for each group to obtain the original data. The embedding algorithm does not introduce error to all data values unlike others fragile techniques and the algorithm controls in the capacity of embedding according to variable called embedding level. The technique proposed is experimentally proved to be resilient against various malicious attacks.
The second scheme is a new reversible robust watermarking algorithm. The proposed algorithm for database protection i.e. proof of ownership and ownership identification based on the secure embedding of blind and multi-bit watermark. It is also based on a multilevel histogram modification algorithm which allows to control in the embedding level and gives high hiding capacity compared to others techniques. At the watermarking detection step, we use the technique of majority voting for the watermark accuracy. Experimental results are also presented to support that it is robust to the important attacks such as adding, deleting and modifying.
This work, providing illustrative examples develop and analyze the proposed algorithms, and present experimental results that evaluate the performance of the algorithms.