JSM 2004 Online Program

Abstract #300326

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Activity Number:	418
Type:	Invited
Date/Time:	Thursday, August 12, 2004 : 10:30 AM to 12:20 PM
Sponsor:	National Institute of Statistical Sciences
Abstract - #300326
Title:	Risk-utility Considerations in Secure Data Integration
Author(s):	Xiaodong Lin*+
Companies:	NISS and SAMSI
Address:	PO Box 14006, Research Triangle Park, NC, 27709-4006,
Keywords:	data integration ; privacy ; secure computation ; disclosure risk ; data utility
Abstract:	We show how techniques from computer science, such as secure summation, and modifications, such as secure data pooling, allow informative analyses of multiple datasets without actually performing any data integration. "Horizontally partitioned regressions" are a prominent example. A risk-utility formulation is proposed for these kinds of problems, and we describe ways in which our procedures are optimal in the sense of maximizing utility, in this case of analyses of the data, subject to constraints on disclosure risk.

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