A Method for Privacy Preserving Mining of Association Rules Based on Web Usage Mining

Abstract

Data mining basing on Privacy preservation has become a research hot point now. Web usage mining is one kind of data mining applications, and how to prevent data leakiness in web usage mining is also an important issue. In this paper, we present an effective method for privacy preserving association rule mining in the web usage mining, Secondary Random Response Column Replacement (SRRCR) to improve the privacy preservation and mining accuracy. Then, a privacy preserving association rule mining algorithm based on SRRCR is presented, which can achieve significant improvements in terms of privacy and efficiency. Finally, we present experimental results that validate the algorithms by applying it on real datasets.