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Improving data utility in differential privacy and k-anonymity
[article]
2013
arXiv
pre-print
We focus on two mainstream privacy models: k-anonymity and differential privacy. Once a privacy model has been selected, the goal is to enforce it while preserving as much data utility as possible. The main objective of this thesis is to improve the data utility in k-anonymous and differentially private data releases. k-Anonymity has several drawbacks. On the disclosure limitation side, there is a lack of protection against attribute disclosure and against informed intruders. On the data
arXiv:1307.0966v1
fatcat:adgnr7mbirbatkeirelc7pj67a