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L-diversity on K-anonymity with External Database for Improving Privacy Preserving Data Publishing
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 54 - Number 14 |
| Year of Publication: 2012 |
| Authors: P. Mayil Vel Kumar, M. Karthikeyan |
10.5120/8632-2341
|
P. Mayil Vel Kumar, M. Karthikeyan . L-diversity on K-anonymity with External Database for Improving Privacy Preserving Data Publishing. International Journal of Computer Applications. 54, 14 ( September 2012), 7-13. DOI=10.5120/8632-2341
Abstract
The data must be secure and measurable at the public when it releases to view. The data table produces personal information and sensitive values. They are maintained for secrecy, the anonymity is the best method to protect the data. There are many anonymity methods to protect the data. k -anonymity is one method to protect the data. The problem in k- anonymity method is if data set increases then utility decreases. Also k- anonymity data is possible to many attacks like Homogeneity Attack, Background Knowledge Attack. The ? -diversity is another method to protect the data. Main advantage of ?- diversity is the data set increases then the data utility also increases. Based on above advantage, we applied ? -diversity concept in k-anonymity applied external data set and we evaluate high efficiency dataset. It shows the ? - diversity reduces the data losses in k anonymity data sets when data point moves any size.
References
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