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

摘要：

Privacy-preserving data mining in distributed or grid environment is an important hot research topic in recent years. WefocusonthePrivacy-preserving sequentialpatternmining 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.

作者: Weimin Ouyang Qinhua Huang

作者单位: Management Department, Shanghai University of Sport Qinyuanhuan Road, 200438 Shanghai, China;School School of Computer Engineering and Science, Shanghai University Yanchang Road, 200072 Shanghai, Chin

会议类型: 国际会议

会议名称: 2006 IEEE International Conference on Information Acquisition

会议地点: 山东威海

会议语种:英文

页码: 149-154

在线出版日期: 2006-08-20（万方平台首次上网日期，不代表论文的发表时间）