Name
Abstract | ||
|---|---|---|
Microaggregation is one of the most commonly employed microdata protection methods. This method builds clusters of at least koriginal records and replaces the records in each cluster with the centroid of the cluster. Usually, when records are complex, i.e., the number of attributes of the data set is large, this data set is split into smaller blocks of attributes and microaggregation is applied to each block, successively and independently. In this way, the information loss when collapsing several values to the centroid of their group is reduced, at the cost of losing the k-anonymity property when at least two attributes of different blocks are known by the intruder.In this work, we present a new microaggregation method called One dimension microaggregation(Mic1D茂戮驴 茂戮驴). This method gathers all the values of the data set into a single sorted vector, independently of the attribute they belong to. Then, it microaggregates all the mixed values together. Our experiments show that, using real data, our proposal obtains lower disclosure risk than previous approaches whereas the information loss is preserved. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-88269-5_20 | MDAI |
Keywords | DocType | Volume |
different block,new microaggregation method,lower disclosure risk,k-anonymity property,dimension microaggregation,information loss,koriginal record,improving microaggregation,microdata protection method,complex record anonymization | Conference | 5285 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
10 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jordi Pont-Tuset | 1 | 656 | 32.22 |
| Jordi Nin | 2 | 311 | 26.53 |
| Pau Medrano-Gracia | 3 | 162 | 14.03 |
| Josep-Ll. Larriba-Pey | 4 | 16 | 2.38 |
| Victor Muntés-Mulero | 5 | 204 | 22.79 |