Hiding
Sensitive Association Rules With Limited Side Effects
ABSTRACT
Data
mining techniques have been widely used in various applications.
Data
mining extracts
novel and useful
knowledge from large repositories of data and has become an effective analysis
and decision means in corporation.
The
sharing of data for data mining can bring a lot of advantages for research and
business collaboration;
However,
large repositories of data contain private data and sensitive rules that must
be protected before published.
Motivated by the multiple conflicting
requirements of data sharing, privacy preserving and knowledge discovery,
privacy preserving data mining has become a research hotspot in data mining and
database security fields.
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