Matheus Silveira
ABSTRACT
Anonymization techniques play a key role in protecting data privacy, especially in a context where more and more personal information is collected and processed. Although anonymization techniques are considered a crucial approach to comply with the aforementioned aspects of privacy laws, these existing anonymization techniques allow for different levels of anonymization, which can change the context of the data, making it impossible to apply smart solution techniques. Within this context, this article presents a cloud service for anonymizing data according to the type of data identified. In addition to the application of existing techniques, the algorithm Clustering Permutation for data Anonymization (CPA) is proposed. Results of experiments using a real cloud environment suggest that the proposed solution is adequate to protect data through data anonymization.
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Index Terms
- An Anonymization Service for Privacy in Data Mining
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