Distributed FP Growth Algorithm for Cloud Platform without Exposing the Individual Transaction Data
Saritha Byreddi1, A. Rama Mohan Reddy2
1Ms Saritha Byreddi, Research Scholar, Department of Computer Science and Engineering, Sri Venkateswara Univrsity, Tirupati.
2Dr.A.Rama Mohan Reddy, Professor, Computer Science and Engineering, SV University College of Engineering, Tirupati.
Manuscript received on 22 August 2019. | Revised Manuscript received on 26 August 2019. | Manuscript published on 30 September 2019. | PP: 4983-4989 | Volume-8 Issue-3 September 2019 | Retrieval Number: C5633098319/2019©BEIESP | DOI: 10.35940/ijrte.C5633.098319
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Data Mining, Association Rules, Privacy Preserving, Patterns.
Scope of the Article: Data Mining