Invertible Matrix-based Privacy-preserving Association Rules Mining
Xiukun Wang · Jisuanji gongcheng · 2009
With the growing concern over data privacy-preserving problem, how to discover association rules from distributed databases becomes one of the hot topics of this field.This paper is devoted to study the problem of discovering global frequent itemsets from distributed vertically partitioned databases with the goal of preserving the confidentiality of each database.All sites are worked together to find global frequent itemsets without revealing private data, each one holds some attributes of global database.The paper presents an invertible matrix-based encryption protocol based on the research of commodity server model, which protocol is of great confidentiality, effectiveness and correctness for distributed vertically partitioned databases.