Privacy-Preserving Two-Party Distributed Association Rules Mining on Horizontally Partitioned Data

@article{Zhang2013PrivacyPreservingTD,
  title={Privacy-Preserving Two-Party Distributed Association Rules Mining on Horizontally Partitioned Data},
  author={Feng Zhang and Chunming Rong and Gansen Zhao and Jinxia Wu and Xiangning Wu},
  journal={2013 International Conference on Cloud Computing and Big Data},
  year={2013},
  pages={633-640}
}
In many applications, data mining has to be done in distributed data scenarios. In such situations, data owners may be concerned with the misuse of data, hence, they do not want their data to be mined, especially when these contain sensitive information. Privacy-preserving Data Mining (PPDM) aims to protect data privacy in the course of data mining. Privacy preserving distributed association rules mining protocols have been developed for horizontally partitioned data scenarios with more than… CONTINUE READING

Similar Papers

Loading similar papers…