Method and apparatus for variable privacy preservation in data mining

Abstract

Improved privacy preservation techniques are disclosed for use in accordance with data mining. By way of example, a technique for preserving privacy of data records for use in a data mining application comprises the following steps / operations. Different privacy levels are assigned to the data records. Condensed groups are constructed from the data records based on the privacy levels, wherein summary statistics are maintained for each condensed group. Pseudo-data is generated from the summary statistics, wherein the pseudo-data is available for use in the data mining application. Principles of the invention are capable of handling both static and dynamic data sets

Description

[0001] This invention was made with Government support under Contract No.: H98230-04-3-0001 awarded by the U.S. Department of Defense. The Government has certain rights in this invention.FIELD OF THE INVENTION [0002] The present invention relates to data mining techniques and, more particularly, to variable privacy preserving, data mining techniques. BACKGROUND OF THE INVENTION [0003] Privacy preserving data mining has become an important issue in recent years due to the large amount of consumer data tracked by automated systems on the Internet. The proliferation of electronic commerce on the World Wide Web has resulted in the storage of large amounts of transactional and personal information about users. In addition, advances in hardware technology have also made it more feasible to track information about individuals from transactions in everyday life. [0004] For example, a simple transaction such as using a credit card results in automated storage of information about user buying...

AI Technical Summary

Benefits of technology

[0007] Principles of the invention provide improved privac...

Problems solved by technology

Privacy preserving data mining has become an important issue in recent years due to the large amount of consumer data tracked by automated systems on the Internet.

In many cases, users are not willing to supply such personal data unless its privacy is guaranteed.

However, while there has been a considerable amount of focus on privacy preserving data collection and mining methods in recent years, such methods assume homogeneity in the privacy level of different entities.

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