The Center for Education and Research in Information Assurance and Security (CERIAS)

The Center for Education and Research in
Information Assurance and Security (CERIAS)
Center for Education and Research in Information Assurance and Security

Privacy-preserving k-means clustering over vertically partitioned data

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Author

Christopher Clifton

Tech report number

CERIAS TR 2003-47

Entry type

conference

Abstract

Privacy and security concerns can prevent sharing of data, derailing data mining projects. Distributed knowledge discovery, if done correctly, can alleviate this problem. The key is to obtain valid results, while providing guarantees on the (non)disclosure of data. We present a method for k-means clustering when different sites contain different attributes for a common set of entities. Each site learns the cluster of each entity, but learns nothing about the attributes at other sites.

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Date

2003 – 08

URL

http://portal.acm.org/citation.cfm?doid=956750.956776

Address

Washington, D.C.

Key alpha

Clifton

Note

The Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining August 24-27, 2003 in Washington, D.C. Honorable Mention, Best Paper Competition

Publication Date

2003-08-01

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