• Ankit jain
• Hitesh Kag

With the development and penetration of data mining within different fields and disciplines, security and privacy concerns have emerged. The aim of privacy-preserving data mining is to find the right balance between maximizing analysis results and keeping the inferences that disclose private information about organizations or individuals at a minimum. In this paper, we proposed the Privacy Preserving Association Rule mining i.e. “PPARM” technique for multiparty computation of privacy-preserving data model for aggregation, cryptographic security, and association rule mining concept. In this process, the data is secured using the cryptographic techniques and for providing the more secure mining technique the server generated random keys are used. Using the proposed technique the data is mined in a similar manner as the association rule mining do, but for securing the data sensitivity the cryptographic technique is used at the client end. After mining of data, the association rules are recoverable at client end also by the similar keys as produced by the server.

Data Mining, Cloud Computing, Association Rule Mining, Apriori, PPDM, PPARM

"PPARM: Privacy Preserving Association Rule Mining Technique for Vertical Partitioning Database", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.138-144, June 2019, Available :http://www.jetir.org/papers/JETIR1906X52.pdf

"PPARM: Privacy Preserving Association Rule Mining Technique for Vertical Partitioning Database", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp138-144, June 2019, Available at : http://www.jetir.org/papers/JETIR1906X52.pdf