Section Article

Investigation into Association Rule Mining with Privacy Preservation
Author(s): Dr. Kishore Jena

Abstract
In recent times there has been a substantial surge in the volume of data being generated and stored. To effectively extract information from the vast quantities of data created by various business applications doing data analysis is crucial. Data mining techniques use a diverse range of tools to extract information about an organisation. Association rule mining is a prominent approach used in data mining. This method is important because it aims to uncover relationships between the many elements of a transaction. Maintaining data security is crucial during the process of association rule mining. This is because it is essential to prevent the disclosure of sensitive information pertaining to the organisation. This paper aims to provide a comprehensive overview of various mining techniques used for protecting privacy in association rule mining. The subject encompasses several methods for safeguarding privacy such as those grounded on heuristics precision boundaries reconstruction and cryptography among others. Furthermore it offers a thorough and coherent exposition of the several performance evaluation criteria used in the ranking of different techniques and the comparative analysis of various methods for privacy-preserving association rule mining.