PRIVACY PRESERVING SEQUENTIAL PATTERN MINING BASED ON SECURE TWO-PARTY COMPUTATION

摘要：

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: two parties, each having a private data set, wish to collaboratively discover sequential patterns on the union of the two private data sets without disclosing their private data to each other. Therefore, we put forward a novel approach to discover Privacy-preserving sequential patterns based on secure two-party computation using homomorphic encryption technology.

关键词： Secure Two-party Computation Sequential Pattern Mining Privacy Preserving

作者: WEI-MIN OUYANG QIN-HUA 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, Chi

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 1227-1232

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）