Protecting Data through 'Perturbation' Techniques: The Impact on Knowledge Discovery in Databases

View Sample PDF

Author(s): Rick L. Wilson (Oklahoma State University, USA)and Peter A. Rosen (Oklahoma State University, USA)
Copyright: 2008
Pages: 12
Source title: Information Security and Ethics: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Hamid Nemati (The University of North Carolina at Greensboro, USA)
DOI: 10.4018/978-1-59904-937-3.ch105

Keywords: Information Science Reference / Information Security & Privacy / IT Security and Ethics / Security & Forensics

Purchase

View Protecting Data through 'Perturbation' Techniques: The Impact on Knowledge Discovery in Databases on the publisher's website for pricing and purchasing information.

Abstract

Data perturbation is a data security technique that adds ‘noise’ to databases allowing individual record confidentiality. This technique allows users to ascertain key summary information about the data that is not distorted and does not lead to a security breach. Four bias types have been proposed which assess the effectiveness of such techniques. However, these biases only deal with simple aggregate concepts (averages, etc.) found in the database. To compete in today’s business environment, it is critical that organizations utilize data mining approaches to discover additional knowledge about themselves ‘hidden’ in their databases. Thus, database administrators are faced with competing objectives: protection of confidential data versus data disclosure for data mining applications. This paper empirically explores whether data protection provided by perturbation techniques adds a so-called data mining bias to the database. The results find initial support for the existence of this bias.

The IRMA Community

Research IRM

Protecting Data through 'Perturbation' Techniques: The Impact on Knowledge Discovery in Databases

Purchase

Abstract

Related Content

IRMA Sponsors