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Research on the Personalized Privacy Preserving Distributed Data Mining

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3 Author(s)
Yanguang Shen ; Sch. of Inf. Sci. & Electr. Eng., Hebei Univ. of Eng., Handan, China ; Hui Shao ; Yan Li

In this paper we studied privacy preserving distributed data mining. The existing methods focus on a universal approach that exerts preservation in the same degree for all persons, without catering for their concrete needs. In view of this we innovatively proposed a new framework combining the secure multiparty computation (SMC) with K-anonymity technology, and achieved personalized privacy preserving distributed data mining based on decision tree classification algorithm. Compared with other algorithms our method could make a good trade-off point between privacy and accuracy, with high efficiency and low-overhead of computing and communication.

Published in:

Future Information Technology and Management Engineering, 2009. FITME '09. Second International Conference on

Date of Conference:

13-14 Dec. 2009

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