PRIVACY PRESERVING SEQUENTIAL PATTERN MINING BASED ON DATA PERTURBATION

摘要：

Data mining is to discover previously unknown, potentially useful and nontrivial knowledge, patterns or rules.Because databases may have some sensitive information which should not be leaked out, it is nontrivial to study data mining techniques without neglecting sensitive information, i.e., privacy-preserving data mining.In this paper, a new technique has been proposed for privacy-preserving mining of sequential patterns based on data perturbation.Experimental results show that the reconstructing support of frequent sequences can achieve a rather high level of accuracy.

关键词： Privacy preserving Data perturbation Data mining

作者: WEI-MIN OUYANG HONG-LIANG XIN QIN-HUA HUANG

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

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 3239-3243

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）