Preventing Disclosure of Sensitive Knowledge by Hiding Inference

Provided by: International Journal of Computer Applications
Topic: Big Data
Format: PDF
'Data mining' is a way of extracting data or uncovering hidden patterns of information from databases. So, there is a need to prevent the "Inference rules" from being disclosed such that the more secure data sets cannot be identified from non-sensitive attributes. This can be done through removing/adding certain item sets in the transactions (Sanitization). The purpose is to hide the Inference rules, so that the user may not be able to discover any valuable information from other non-sensitive data and any organization can release all samples of their data without the fear of 'Knowledge discovery In databases' which can be achieved by investigating frequently occurring item sets, rules that can be mined from them with the objective of hiding them.

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