Science Publishing Group
Association rules mining is a frequently used technique which finds interesting association and correlation relationships among large set of data items which occur frequently together. Now-a-days, data collection is ubiquitous in social and business areas. Many companies and organizations want to do the collaborative association rules mining to get the joint benefits. However, the sensitive information leakage is a problem the authors have to solve and privacy-preserving techniques are strongly needed. In this paper, they focus on the privacy issue of the association rules mining and propose a secure Frequent-Pattern tree (FP-tree) based scheme to pre-serve private information while doing the collaborative association rules mining.