Using Safety Constraint for Transactional Dataset Anonymization

Abstract : In this paper, we address privacy breaches in transactional data where individuals have multiple tuples in a dataset. We provide a safe grouping principle to ensure that correlated values are grouped together in unique partitions that enforce l-diversity at the level of individuals. We conduct a set of experiments to evaluate privacy breach and the anonymization cost of safe grouping.
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Communication dans un congrès
Lingyu Wang; Basit Shafiq. 27th Data and Applications Security and Privacy (DBSec), Jul 2013, Newark, NJ, United States. Springer, Lecture Notes in Computer Science, LNCS-7964, pp.164-178, 2013, Data and Applications Security and Privacy XXVII. 〈10.1007/978-3-642-39256-6_11〉
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Dernière modification le : jeudi 16 mars 2017 - 09:24:25
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Bechara Bouna, Chris Clifton, Qutaibah Malluhi. Using Safety Constraint for Transactional Dataset Anonymization. Lingyu Wang; Basit Shafiq. 27th Data and Applications Security and Privacy (DBSec), Jul 2013, Newark, NJ, United States. Springer, Lecture Notes in Computer Science, LNCS-7964, pp.164-178, 2013, Data and Applications Security and Privacy XXVII. 〈10.1007/978-3-642-39256-6_11〉. 〈hal-01490703〉

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