期刊名称：International Journal of Operations and Logistics Management
印刷版ISSN：2309-8023
电子版ISSN：2310-4945
出版年度：2014
期号：2
页码：140-147
语种：English
出版社：Academy of Business & Scientific Research
摘要：For making the decision of data mining process some expertise are required, some organization have their own expertise, but many organization doesn’t have their own expertise, so the organization helps with some external advisor for the process of data mining. But risk is occurred at the time of getting advice from the external advisor; the question arises regarding the privacy of the customer data and loss of business intelligence. The Security and Privacy of the data are main challenging issues. The owner of the data has some private property like the outsourced database which contains the association rules. However, if the service provider is not trustworthy then integrity of mining results can affect badly. The proposed scheme for privacy preserving mining on databases to protect association rule means the corporate privacy. As per our study, in our paper we are proposing the heuristic based algorithm for hiding the sensitive association rules the algorithm is named as MDSRRC , owner hide sensitive association rule and place transform rules to the server for outsourcing purpose. In this algorithm we are providing an incremental association rule for mining. The recent study concludes that the problem of the incremental association rule mining task’s importance was observed, when data is updated. The Matrix Apriori algorithm is proposed which is based on analysis of two association algorithm named as Apriori algorithm and FP-growth algorithm. The matrix Apriori algorithm has a simple structure similar as a matrices and vectors; the algorithm generates frequent patterns and minimizes the number of sets, as compared to previous algorithm. The matrix algorithm is simple and efficient way to generate association rule than the previous algorithm. For hiding the sensitive information of the database proposed algorithm MDSSRC selects the transactions and items by using certain criteria which transform. As per comparing with the previous algorithm the proposed algorithm is much better in performance which can be concluded with the results of the implementation.
