Enhanced Association Rule hiding for Privacy Preservation

Abstract

Data mining is a technologically driven process of using algorithms, techniques to newlineanalyse data from multiple perspectives and extract meaningful patterns, ultimately newlinefacilitating decision-making. Organizations generally prefer data or knowledge sharing with others in order to obtain mutual benefits, which raises privacy concerns. Sharing data with a third party brings the risk of disclosing sensitive knowledge contained in it, thus endangering newlinethe security and privacy of individuals and organizations. Sensitive information or knowledge newlinemust be hidden from unauthorized access before releasing or publishing the dataset. Privacy preserving data mining techniques give new direction to solving this issue. Privacy preserving data mining algorithms are developed for modifying the original data such that newlinesensitive data and knowledge remain unrevealed even after the mining process. These algorithms are analysed for the side-effects they incur during the process of privacy preservation. newlineAssociation rule mining is the information mining interaction of finding the principles newlinethat administer correlations and associations between sets of database items from various newlinekinds of databases. Sharing association rules has been shown to be advantageous in business newlinecollaboration, although privacy precautions are required. One may choose to reveal only a newlineportion of their knowledge while keeping strategic patterns known as sensitive rules hidden. newlineThese sensitive regulations must be safeguarded before being shared, as they are critical for newlinestrategic decisions and must stay confidential. Some businesses prefer to disclose their data in newlineorder to collaborate, while others prefer to simply share the patterns that their data has newlinerevealed. The problem here is figuring out how to secure the sensitive rules without newlinejeopardising the effectiveness of data mining as a whole. Association rule hiding is a privacy newlinepreservation technique to hide sensitive association rules.