Distributed FP Growth Algorithm for Cloud Platform without Exposing the Individual Transaction Data

Data mining is a concept of extracting the required patterns to take appropriate decisions. One of the major challenges in data mining is to extract hidden patterns with the secure and privacy from the huge databases. Privacy preserving is a method used to extract hidden patterns with privacy. In this paper Mining Association rules with privacy preserving mechanism in the cloud platform is proposed. It is a powerful technique to find the hidden pattern in the distributed database. For now many mechanisms has proposed but it has many drawback, not proven and not specific. In cloud the data is stored in the servers. The data is distributed in different servers in cloud platform. Each server has one of the transaction data. The current paper proposed the distributed FP growth algorithm for cloud platform without exposing the individual transaction data. The results proved that the proposed algorithm is best to extract hidden pattern from Cloud platform in terms of efficiency.