Name
Abstract | ||
|---|---|---|
Data publishing is a challenging task from the privacy point of view. Different anonymization techniques are proposed in the literature to preserve privacy in accordance with some mathematical constraints. Disassociation is one of the anonymization techniques that relies on the km - anonymity privacy constraint to guarantee a certain level of privacy for set-valued datasets (e.g., search and shopping items). Dis-association separates a set-valued dataset by clustering the dataset into groups of records with common frequent items, and then splitting each cluster into record chunks respecting km - anonymity. In this paper, we define a new ant-based clustering algorithm based on the disassociation technique to keep some of the items associated together throughout the anonymization process. We define these associations as utility rules that should be treated with eagerness while anonymizing the data. We perform a set of experiments to evaluate our algorithm w.r.t. these utility rules.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3331076.3331084 | Proceedings of the 23rd International Database Applications & Engineering Symposium |
Keywords | DocType | ISBN |
anonymization, ant colony clustering, disassociation, privacy, utility | Conference | 978-1-4503-6249-8 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nancy Awad | 1 | 0 | 0.34 |
| Jean-François Couchot | 2 | 80 | 18.33 |
| Béchara Al Bouna | 3 | 45 | 11.20 |
| Laurent Philippe | 4 | 71 | 12.95 |