Advanced models for the protection of numerical information in databases: Providing security and flexibility in markets for private information

Date of Completion

January 2004

Keywords

Business Administration, Management|Information Science

Degree

Ph.D.

Abstract

A practical method for giving unlimited, correct, numerical responses to ad-hoc queries to an on-line database, while not compromising confidential numerical data, has been developed by (Gopal et al. 2002) and is called Confidentiality via Camouflage (CVC). Responses are in the form of intervals that are guaranteed to contain the exact answer. Virtually any imaginable query type can be answered and although sharing of query answers among users presents no problem, the threat of insider information is real. In this work we identify two distinct types of insider information, depending on whether the knowledge is of data in the confidential field or of the algorithmic process that is used to answer queries. We show that different realizations of CVC can protect against one type of insider threat or the other, while a combination of realizations can be used if the database administrator is not able to specify the type of threat that is present. Various strategies for dealing with cases where a user poses both types of threats are also presented. Computational experience relates the degradation of answer intervals that can be expected based on the type of threat that is protected against and indicates that, in general, algorithmic threat causes the greatest degradation. In addition we show that a new realization of CVC (CVC-Star) enables the development of a model for compensating subjects whose privacy requirements may not be satisfied when a database user requests, and is supplied with, a query answer with a reduced interval range. ^

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