A Survey on the Privacy Preserving Algorithm of Association Rule Mining
Yongcheng Luo, Yan Zhao, Jiajin Le · 2009
We provide an overview of privacy preserving association rule mining, which is one of the most popular pattern-discovery methods in the new and rapidly emerging research area of privacy preserving data mining. Various proposals and algorithms have been designed for it in recent years. In this paper, we summarize them and survey current existing techniques, and analyze their advantage and disadvantage. We divide the proposals of privacy preserving association rule mining into three categories: heuristic-based techniques, reconstruction-based techniques, cryptography-based techniques. Then we give a simple review of the work accomplished. Finally, we conclude further research directions of privacy preserving algorithms of association rule mining by analyzing the existing work.