High Privacy for Data Disclosers

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Provided by: International Journal for Development of Computer Science & Technology (IJDCST)
Topic: Big Data
Format: PDF
Now-a-days micro data publishing is very useful to the all the organizations that enables researchers and policy-makers to analyze the data and learn important information. Privacy is a one of the most important factor here. One of the existing methods for privacy measures such as k-anonymity protects against identity disclosures, but it is not providing affective protection against attribute disclosures. Another privacy measure is l-diversity attempts to solve this problem. But it is not enough nor efficient to prevent attribute disclosures and fails at data utilization.
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