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K-anonymous Mathematical Model Based on Greedy Algorithm
- 1 Hangzhou Dianzi University
* Author to whom correspondence should be addressed.
Abstract
This research propose a user-centered combinatorial data anonymization method. whereas a data matrix is said to be k-anonymous if each row occurs at least k times. Therefore, the authors propose PATTERN-GUIDED k-ANONYMITY, an improved k-anonymization problem. It allows users to designate the combinations in which suppressions may occur, building on prior work and addressing relevant shortcomings. Users of anonymous data can indicate that the aspects of the data are valued differently. The so-called K-anonymity is usually realized by Generalization and Suppression techniques. Generalization refers to Generalization and abstraction of data so that specific values cannot be distinguished, for example, the age data group can be generalized into an age group.
Keywords
K-modes clustering, greedy algorithm, K-anonymity, hiding distance
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Cite this article
Chen,S. (2023). K-anonymous Mathematical Model Based on Greedy Algorithm. Applied and Computational Engineering,8,55-60.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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