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Privacy-Preserving Data Publishing (Paperback)
Loot Price: R835
Discovery Miles 8 350
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Privacy-Preserving Data Publishing (Paperback)
Series: Synthesis Lectures on Data Management
Expected to ship within 10 - 15 working days
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Privacy preservation has become a major issue in many data analysis
applications. When a data set is released to other parties for data
analysis, privacy-preserving techniques are often required to
reduce the possibility of identifying sensitive information about
individuals. For example, in medical data, sensitive information
can be the fact that a particular patient suffers from HIV. In
spatial data, sensitive information can be a specific location of
an individual. In web surfing data, the information that a user
browses certain websites may be considered sensitive. Consider a
dataset containing some sensitive information is to be released to
the public. In order to protect sensitive information, the simplest
solution is not to disclose the information. However, this would be
an overkill since it will hinder the process of data analysis over
the data from which we can find interesting patterns. Moreover, in
some applications, the data must be disclosed under the government
regulations. Alternatively, the data owner can first modify the
data such that the modified data can guarantee privacy and, at the
same time, the modified data retains sufficient utility and can be
released to other parties safely. This process is usually called as
privacy-preserving data publishing. In this monograph, we study how
the data owner can modify the data and how the modified data can
preserve privacy and protect sensitive information. Table of
Contents: Introduction / Fundamental Concepts / One-Time Data
Publishing / Multiple-Time Data Publishing / Graph Data / Other
Data Types / Future Research Directions
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