Privacy Preserving Data Mining Using Association Rule With Condensation Approach
Supriya S. Borhade, Bipin Balu Shinde · 2014
Abstract—With the rapid development data mining within various fields and security and privacy concerns come into view. In data mining while releasing micro-data or patterns from large databases individual or organizational private data may get compromise the information. The main aim behind privacy preserving data mining is to maximizing analysis outcome and minimizing disclosure of individuals or organizational private data. Association rule mining explores interesting relationship between data. This paper is based on concepts: condensation method and association rule. SMC (secure multiparty computation) securely transferring data over the network with hiding process which hide sensitive association rule which create threat to privacy. Now privacy preserving data mining has become increasingly popular because it provides sharing of private or sensitive data for analysis purposes. Most of people and organizations are afraid or hesitate to share their data or refusing to share their data or sometimes might provide wrong data. Due to rapid proliferation of private information on the internet, lot of research has been done in recent years for privacy preserving data mining. Users are unwilling to provide private or personal data unless and until privacy is assured. Sometimes automated transaction system holds or track information about individuals in day today’s life. For example credit card transactions.