Detecting Inconsistencies in Private Data With Secure Function Evaluation

Erroneous and inconsistent data, often referred to as 'Dirty data', is a major worry for businesses. Prevalent techniques to improve data quality consist of discovering data quality rules, identifying records that violate those rules, and then modifying the data to either remove those violations. Most of the paper described in the literature deals with cases where both the data and the rules are visible to the party that is in charge of cleaning the data.

Provided by: Purdue University Topic: Security Date Added: Feb 2011 Format: PDF

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