Hierarchical Infrastructure for Large-Scale Distributed Privacy-Preserving Data Mining

Abstract. Data Mining is often required to be performed among a number of groups of sites, where the precondition is that no privacy of any site should be leaked out to other sites. In this paper, a hierarchical infrastructure is proposed for large-scale distributed Privacy Preserving Data Mining (PPDM) utilizing a synergy between P2P and Grid. The proposed architecture is characterized with (1) its ability for preserving the privacy in data mining; (2) its ability for decentralized control; (3) its dynamic and scalable ability; (4) its global asynchrony and local communication ability. An algorithm is described to show how to process large-scale distributed PPDM based on the infrastructure. The remarks in the end show the effectiveness and advantages of the proposed infrastructure for large-scale distributed PPDM.

• Type: Conference
• Year: 2005
• Where: ICCS
• Authors: Jinlong Wang, Congfu Xu, Huifeng Shen, Yunhe Pan
• Keywords: Data Mining, ICCS 2005, Large-scale Distributed Ppdm, Privacy Preserving Data Mining