BibTeX:

@article{IJIRSTV1I9067,
     title={Privacy Preserving Distributed Data Mining Techniques},
     author={Tank Mayurkumar Bhagavanjibhai and Tushar A. Champaneria},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={1},
     number={9},
     pages={202--206},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV1I9067.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

The aim of Privacy Preserving Distributed Data Mining is to extract relevant knowledge from large amount of data while protecting at the same time sensitive information. Due to personal interests, medical databases or business interest privacy is needed. Due to privacy infringement while performing the data mining operation this not often possible to utilize large databases for scientific or financial research. For better decision making we need to perform multi-party computation by combining the database of two or more than two parties, which cannot guarantee security. To address this problem, several privacy preserving data mining techniques are used. In this survey paper, various privacy preserving techniques are reviewed and, also open challenges related to privacy when performing data mining are discussed.

Privacy preserving distributed data mining, PPDDM, Secure Data Mining, PPDM, multi-party data mining