Section Article

Investigation of the preservation of privacy in association rule mining.
Author(s): Dr. Deepak Verma

Abstract
An enormous surge in the generation and retention of data has taken place in recent years. It is important to scrutinise vast quantities of data in order to extract insight since several business applications create this data. Data mining techniques provide firms significant insights via the use of diverse technology. Association rule mining is a prominent approach in the field of data mining. Its main objective is to discover connections or associations between different pieces of transactional data. Ensuring data security is crucial throughout the rule mining process to prevent the disclosure of sensitive information held by the association. This research aims to examine several methods used for safeguarding privacy in association rule mining. The text covers many strategies for preserving privacy such as those based on heuristics precision boundaries reconstruction and cryptography. Furthermore it offers a thorough examination of several techniques for maintaining privacy in association rule mining along with a range of metrics used to analyse the effectiveness of these strategies.