Privacy-preserving data mining /

Bibliographic Details
Main Author:	Zhang, Nan
Other Authors:	Chen, Jianer (Thesis advisor), Zhao, Wei, 1953- (Thesis advisor)
Format:	Thesis eBook
Language:	English
Published:	[College Station, Tex.] : [Texas A&M University], [2010]
Subjects:	Major computer science. Privacy Data Mining
Online Access:	Link to OAK Trust copy

Description
Abstract:	In the research of privacy-preserving data mining, we address issues related to extracting knowledge from large amounts of data without violating the privacy of the data owners. In this study, we first introduce an integrated baseline architecture, design principles, and implementation techniques for privacy-preserving data mining systems. We then discuss the key components of privacy-preserving data mining systems which include three protocols: data collection, inference control, and information sharing. We present and compare strategies for realizing these protocols. Theoretical analysis and experimental evaluation show that our protocols can generate accurate data mining models while protecting the privacy of the data being mined.
Item Description:	"Major Subject: Computer Science" Title from author supplied metadata (automated record created 2010-03-12 12:08:51). Electronic resource.
Physical Description:	1 online resource.
Bibliography:	Includes bibliographical references.