A privacy preservation masking method to support business collaboration.
This paper introduces a privacy preservation masking method to support business collaboration, called Dimensionality Reduction-Based Transformation (DRBT). This method relies on the intuition behind random projection to mask the underlying attribute values subject to cluster analysis. Using DRBT, data owners are able to find a solution that meets privacy requirements and guarantees valid clustering results. DRBT was validated taking into account five real datasets. The major features of this method are: a) it is independent of distance-based clustering algorithms; b) it has a sound mathematical foundation; and c) it does not require CPU-intensive operations.
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| Formato: | Anais e Proceedings de eventos biblioteca |
| Idioma: | English eng |
| Publicado: |
2006-04-19
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| Materias: | Segurança da informação, Sistemas computacionais, Colaboração, Preservação da privacidade, Privacy preservation., Informática, Information, |
| Acceso en línea: | http://www.alice.cnptia.embrapa.br/alice/handle/doc/8731 |
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