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oai:www.ideals.illinois.edu:2142/84538 2023-07-11 col_2142_5131 col_2142_14791 com_2142_5130 com_2142_14790 com_2142_9216

Shaw, Michael J. Li, Jingquan 2015-09-25T22:21:32Z 2015-09-25T22:21:32Z 10000-01-01 2004 2004 The study presents some effective privacy-enhancing transformation techniques that are applicable to various data types. The techniques are able to retain privacy while accessing the information contained in the original data. Specifically, we address the issue of privacy protection through using the data filter, partitioning, synthetic data, and randomization methods. We give examples of inducing the decision-tree classifiers and building detection models of fraud from training data in which the values of sensitive attribute values have been modified. We experimentally validate the privacy-enhancing techniques and the measurement methodology over both real world and synthetic datasets. The experimental results show that the application of privacy-enhancing techniques can preserve the data privacy with minimum loss of information. The results also demonstrate that the proposed techniques can achieve comparative performance measures or mining results while preserving the data privacy. Made available in DSpace on 2015-09-25T22:21:32Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3160914.pdf: 5640815 bytes, checksum: 9c62e7c6da47d69ba52db6a2acdb064e (MD5) Previous issue date: 2004 Embargo set by: Seth Robbins for item 85819 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only 121 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2004. http://hdl.handle.net/2142/84538 (MiAaPQ)AAI3160914 eng Business Administration, Management Privacy -Enhancing Data Mining: Issues, Techniques and Measures text Business Administration Business Administration University of Illinois at Urbana-Champaign Dissertation Ph.D.