(k, l)-Clustering for Transactional Data Streams Anonymization
In this paper, we address the correlation problem in the anonymization of transactional data streams. We propose a bucketization-based technique, entitled (k, l)-clustering to prevent such privacy breaches by ensuring that the same k individuals remain grouped together over the entire anonymized str...
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| Other Authors: | , , , |
| Format: | conferenceObject |
| Published: |
2018
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10725/10229 https://doi.org/10.1007/978-3-319-99807-7_35 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://link.springer.com/chapter/10.1007/978-3-319-99807-7_35 |
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