Hiding a Needle in a Haystack

In the last few years, Hadoop become a "de facto" standard to process large scale data as an open source distributed system. With combination of data mining techniques, Hadoop improve data analysis utility. That is why, there are amount of research is studied to apply data mining technique to mapreduce framework in Hadoop. However, data mining have a possibility to cause a privacy violation and this threat is a huge obstacle for data mining using Hadoop. To solve this problem, numerous studies have been conducted. However, existing studies were insufficient and had several drawbacks. In this paper, we propose the privacy preserving data mining technique in Hadoop that is solve privacy violation without utility degradation. We focus on association rule mining algorithm that is representative data mining algorithm. We validate the proposed technique to satisfy performance and preserve data privacy through the experimental results.