An Efficient Approach for Privacy Preserving Distributed Mining of Association Rules in Unsecured Environment

Distributed data mining techniques are widely used for many applications viz; marketing, decision making, statistical analysis etc. In distributed data environment, each of the involving sites contains local information which will be collaborated to extract global mining result. However, these techniques have been investigated in terms of privacy and security concerns of individual site's information. To solve this problem, many cryptography techniques have been investigated. Still there is a room for further improvement. In this paper, we propose an efficient approach for privacy preserving distributed association rule mining. We use onion routing protocol in order to exchange information among involving sites. We use an elliptic curve (EC) based cryptography in order to achieve security and privacy of individual site's information in unsecured distributed environment. Finally, we analyze proposed solution in terms of security, privacy, computational cost and communication cost.