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Fine-Grain Perturbation for Privacy Preserving Data Publishing
- Source :
- ICDM
- Publication Year :
- 2009
- Publisher :
- IEEE, 2009.
-
Abstract
- Recent work [12] shows that conventional privacy preserving publishing techniques based on anonymity-groups are susceptible to corruption attacks. In a corruption attack, if the sensitive information of any anonymity-group member is uncovered, then the remaining group members are at risk. In this study, we abandon anonymity-groups and hide sensitive information through perturbation on the sensitive attribute. With each record being perturbed independently, corruption attacks cannot be effectively carried out. Previous anti-corruption work did not minimize information loss. This paper proposes to address this issue by allowing fine-grain privacy specification. We demonstrate the power of our approach through experiments on real medical and synthetic datasets.
- Subjects :
- Information privacy
Fine grain
business.industry
Computer science
Corruption
media_common.quotation_subject
Data_MISCELLANEOUS
Human immunodeficiency virus (HIV)
Data publishing
Computer security
computer.software_genre
medicine.disease_cause
Privacy preserving
Information sensitivity
medicine
Electronic publishing
Data mining
business
computer
media_common
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2009 Ninth IEEE International Conference on Data Mining
- Accession number :
- edsair.doi...........786ff02251fd9d416761f22dee608e6e