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Abstract: Classi cation mining algorithms can be used to discover protected values from nonsensitive data. We reported earlier on the development of an evaluation algorithm, along with a set of security policies, for use in analyzing a protected data element's risk of disclosure with respect to decision-region based algorithms. This paper presents an extension of the previous work. Speci cally, the development of two new algorithms for evaluating a protected data element's risk of disclosure with... (Update)
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BibTeX entry: (Update)
@misc{ johnsten-security,
author = "Tom Johnsten and Vijay V. Raghavan",
title = "Security Procedures for Decision- and Extended Decision-Region Based Mining
Algorithms",
url = "citeseer.ist.psu.edu/695205.html" }
Citations (may not include all citations):2177 Programs For Machine Learning (context) - Quinlan - 1993
201 Relevance Weighting for Search Terms (context) - Robertson, Jones - 1976
47 Data Mining: The Search for Knowledge in Databases - Holsheimer, Siebes - 1994
5 Protecting Against Data Mining Through Samples (context) - Clifton - 1999
4 Parsimonious Downgrading and Decision Trees Applied to the I.. - Chang, Moskowitz - 1998
4 An Integrated Framework for Database Privacy Protection - Chang, Moskowitz - 2000
1 Impact of Decision-Region Based Classi cation Mining Algorit.. (context) - Johnsten, Raghavan - 1999
1 CART User Manual (context) - Steinberg, Colla - 1997
1 and Marks (context) - Clifton - 1996
http://fas.sfu.ca/cs/people/Grad
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