Open AccessDistributed FP Growth Algorithm for Cloud Platform without Exposing the Individual Transaction Data
Author(s) -
Ms Saritha Byreddi*,
D Arunkumar Reddy
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.c5633.098319
Subject(s) - cloud computing , computer science , server , association rule learning , database transaction , cloud server , data mining , distributed database , distributed transaction , distributed computing , database , information privacy , transaction data , transaction processing , computer security , computer network , operating system
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.