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Privacy Preserving Sequential Pattern Mining Based on Secure Multi-party Computation

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2 Author(s)
Weimin Ouyang ; Management Department, Shanghai University of Sport, Qinyuanhuan Road, 200438 Shanghai, China; School of Computer Engineering and Science, Shanghai University, Yanchang Road, 200072 Shanghai, China, ; Qinhua Huang

Privacy-preserving data mining in distributed or grid environment is an important hot research topic in recent years. We focus on the privacy-preserving sequential pattern mining in the following situation: multiple parties, each having a private data set, wish to collaboratively discover sequential patterns on the union of the their private data sets respectively without disclosing their private data to any other party. Therefore, we put forward a novel approach to discover privacy-preserving sequential patterns based on secure multi-party computation using homomorphic encryption technology

Published in:

2006 IEEE International Conference on Information Acquisition

Date of Conference:

20-23 Aug. 2006