Research on the Random Corresponding of Privacy Data Mining in the Association Rules of Cloud Computing

To strengthen data privacy protection, and improve data mining accuracy, random response mode is adopted to design privacy protection mining method based on association rules. Granular computing method and technology are applied to mining fields of association rules in data mining, and mining to association rules is researched in more extensive way from another perspective in this paper. Firstly, partial concealing mode is adopted to conceal and transform original privacy data and improve data security; secondly, associated frequent item set is utilized to construct simple and efficient privacy protection mining algorithm; finally, algorithm proposed is verified to have higher privacy and accuracy through theoretical analysis and experimental verification. After classical association rules mining algorithm is analyzed and researched in detail with its characteristics and restrictions summarized through examples in this paper, association rules mining model based on granular computing is proposed, which makes theoretical preparation for proposal and construction of association rules pick-up algorithm based on granular computing. Experimental result shows that association rules mining method based on granular computing is feasible and effective.