Sanitization Techniques used in Preserving Sensitive data(.doc)
Abstract:-The discovery of association rules from lager databases has proven beneficial for companies since such rules can be very effective in revealing actionable knowledge that leads to strategic decisions. In tandem with this benefit, association rule mining can also pose a threat to privacy protection.
The main problem is that from non-sensitive information or unclassified data, one is able to infer sensitive information, including personal information, facts, or even patterns that are not supposed to be disclosed. This scenario reveals a pressing need for techniques that ensure privacy protection, while facilitating proper information accuracy and mining.
In this paper, we present the different sanitization algorithms which are used for balancing privacy and knowledge discovery in association rule mining.
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