Frontiers in Computer Education Wang (ed.)
© 2015 Taylor & Francis Group, London, ISBN 978-1-138-02797-8
A study in watermarking relational databases based on genetic algorithms
Qingtao Wu
School of Art & Design, Zhengzhou Institute of Aeronautical Industry Management, Zhengzhou, China
Pengsong Duan
Zhengzhou University Software Institute, Zhengzhou, China
Jinfa Shi
Zhengzhou Institute of Aeronautical Industry Management, Zhengzhou, China
ABSTRACT: This paper studies a novel scheme of watermarking relational databases for copyright protection
based on genetic algorithms. In this algorithm, a GA is used in a watermark signal processes, and associated
novel watermark insertion algorithms and detection algorithms are proposed. Thus, the watermark signal in this
method is expected to be more meaningful and has closer correlative relationship to the copyright holder. The
experimental results verify that the proposed algorithm is feasible, effective, and robust.
Relational database watermarking protects the intel-
lectual property in today’s internet-based application
environments and in many content distribution appli-
cations. We present a mechanism for proof of own-
ership based on the secure embedding of a robust
imperceptible optimization watermark in relational
database. Based on the rational database watermark,
researches in database watermarks are being con-
ducted by people such as R. Agrawal and R. Sion.
Including previous research into watermarking, they
pay attention to arithmetic embedding and extracting.
A Genetic Algorithm (GA) is a search technique
that is based on the principles of natural selection or
survival of the fittest. Genetic algorithms are one of
the best ways to solve a problem about which little is
known objectively and functions directly in the search.
Then, by using evolving operations such as crossover,
mutation, and selection, the GA creates successive
generations of solutions that evolve and inherit the pos-
itive characteristics of their parents and thus gradually
approach optimal or near-optimal solutions. By using
the objective function directly in the search, GAs can
be effectively applied in nonconvex, highly nonlinear,
and complex problems.
The main contributions to this work include: pre-
senting an effective GA technique to generate water-
mark signal; and present a new technique to insert
and detect watermarks using a mark bit position,
together with a decision-making algorithm by pattern
matching. In order to improve robustness, the scheme
embeds a watermark into the database for several times
and recovers the detected watermark by a majority
voting mechanism.
In this section, the watermark embedding and extrac-
tion algorithms are presented. We assume that some
minor changes of some attributes values can be toler-
ated. And we will embed copyright information into
these attributes. We consider the character copyright
information as a sequence of 0 and 1, the marks of 0 and
1 are small errors in the relational data. All the marks
of 0 and 1 represent integrated copyright information.
The problem of watermarking relational databases can
be modelled as follows.
Suppose relation R contains a primary key P and
numerical attributes A0, A1,…, Av-1. Assume that it
is acceptable to change one of ξ Least Significant
Bits (LSB). Copyright information which will con-
vert as a sequence of 0 and 1 is to be embedded into
relation R for the purpose of copyright protection.
Table 1 summarizes the important parameters used in
our algorithms.
Our technique aims to mark only numeric attributes.
The data owner is responsible for deciding which
attributes are suitable for marking. He also helps
to decide two important parameters ξ and γ, which
describe the limits of modification to a database. We
also suppose the adversary should not remove or mod-
ify the primary key attributes for the integrity and
availability of the database. An attacker cannot guess

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