Significance of Term Relationships on Anonymization

Sharing data provides great benefit to the research community. But disclosing identifiable, sensitive information such as medical records can cause irreparable damage. A number of methods have been proposed to anon Mize sensitive information. With some approaches, term relationships in the data may...

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Bibliographic Details
Published in2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology Vol. 3; pp. 253 - 256
Main Authors Anandan, B., Clifton, C.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2011
Subjects
Cancer
Correlation
Data mining
Liver
Lungs
Pain
Privacy
Semantics
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ISBN9781457713736
145771373X
DOI10.1109/WI-IAT.2011.240

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Summary:Sharing data provides great benefit to the research community. But disclosing identifiable, sensitive information such as medical records can cause irreparable damage. A number of methods have been proposed to anon Mize sensitive information. With some approaches, term relationships in the data may help to re-identify the original data given the de-identified data. This papers studies the significance of correlation in data and then analyzes the effect on anonymization techniques including t-plausibility and k-manonymity. Finally, we show how to address correlation in thet-plausibility model.
ISBN:9781457713736
145771373X
DOI:10.1109/WI-IAT.2011.240