Association rule hiding is the process of transforming a transaction database into a sanitized
version to protect sensitive knowledge and patterns. The challenge is to minimize the side …

Privacy preserving data mining has been recently introduced to cope with privacy issues
related to the data subjects in the course of the mining of the data. It has also been …

Association rule hiding is an efficient solution that helps enterprises avoid the risk caused by
sensitive knowledge leakage when sharing data in their collaborations. This study examines …

Various data mining techniques can be used to discover useful knowledge from large
collections of data. However, there is a risk of disclosing sensitive information when data is …

Privacy preserving data mining is a new research field that aims to protect the private
information and avoid the leakage of this information during the data mining process. One of …

Retailers have been sharing transactional data with supply chain partners for a long time to
the benefit of all involved. However, many are still reluctant to share, and there is evidence …

When data mining techniques are applied to discover useful knowledge behind a large data
collection, they are often required to preserve some confidential information, such as …

This research presents an approach to protect personally identifiable information in
compliance with the national and European institutional data protection framework in a way …

Nowadays, extensively obtainable personal data has made Privacy-Preserving Data Mining
(PPDM) issues a significant one. PPDM handles securing the privacy of sensitive knowledge …

Association rule hiding has been playing a vital role in sensitive knowledge preservation
when sharing data between enterprises. The aim of association rule hiding is to remove …