Closeness: Privacy Measure for Data Publishing Using Multiple Sensitive Attributes

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Provided by: IJESAT (International Journal of Engineering Science & Advanced Technology)
Topic: Big Data
Format: PDF
Data anonymization techniques based on the k-anonymity model have been the focus of intense research in the last few years. However, existing anonymization techniques all assume each tuple in the micro data table contains one single sensitive attribute, while none paid attention to the case of multiple sensitive attributes in a tuple (the MSA case). When releasing micro data, it is necessary to prevent the sensitive information of the individuals from being disclosed. Two types of information disclosure have been identified in the literature. Identity disclosure and attribute disclosure.
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