Privacy Preservation: Chi Square Computation for Association Rule Mining

Raghvendra Kumar, Prasant Kumar Pattnaik, Yogesh Sharma


The big trouble of privacy preservation in data mining techniques has been studied comprehensively in current passing years because of the improved amount of private information which are presents locally and globally in the distributed database environments. The high amount of privacy preservation transformations use some form of data perturbation or representational ambiguity in order to reduce the risk of identification and security as well as privacy. In this paper, we propose an algorithm that is applicable all partitioned database may be horizontal, vertical and hybrid partitioning. The proposed algorithm provides the highest privacy preservation to the all database, because we used the data modification concept with the help of Chi Square concept and after that we used the privacy preservation algorithm to provide the privacy to the distributed homogeneous database by selecting the random number by all parties, then calculate the global support by using the algorithm that mentioned in the paper, with high privacy and zero percentage of data leakage.  

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