A Privacy Preserving Algorithm for Mining Distributed Association Rules
Yuquan Zhu, Yang Tang, Geng Chen · 2011
For resolving the problem that the existing protocol of secure two-party vector dot product computation has the low efficiency and may disclose the privacy data, a method which is effective to find frequent item sets on vertically distributed data is put forward. The method uses semi-honest third party to participate in the calculation, put the converted data of the parties to a third party to calculate. The results show that compared to the original Vector dot product algorithm, the method can obviously improve the algorithm efficiency and accuracy of the results at the precondition that assured the data privacy of all parties.