In this article, we introduce a new and general privacy framework called Pufferfish. The
Pufferfish framework can be used to create new privacy definitions that are customized to the …

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 …

In this paper we introduce a new and general privacy framework called Pufferfish. The
Pufferfish framework can be used to create new privacy definitions that are customized to the …

Protecting the privacy of healthcare information is an important part of encouraging data
custodians to give accurate records so that mining may proceed with confidence. The …

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 …

In big data era, the collected data usually contains rich information and hidden knowledge.
Utility-oriented pattern mining and analytics have shown a powerful ability to explore these …

In this paper, we propose a novel, exact border-based approach that provides an optimal
solution for the hiding of sensitive frequent itemsets by (i) minimally extending the original …

Abstract Association Rule Hiding (ARH) is the process of protecting sensitive knowledge
using data transformation. Although there are some evolutionary-based ARH algorithms …

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 …

High-utility itemset mining has evolved as an essential and captivating research topic. It
aims to extract the patterns/itemsets having high utility value; hence, they are called high …