Baig, Muzammil M. and Li, Jiuyong and Liu, Jixue and Wang, Hua (2011) Cloning for privacy protection in multiple independent data publications. In: CIKM 2011: 20th ACM Conference on Information and Knowledge Management , 24-28 Oct 2011, Glasgow, United Kingdom.
Data anonymization has become a major technique in privacy preserving data publishing. Many methods have been proposed to anonymize one dataset and a series of datasets of a data owner. However, no method has been proposed for the anonymization of data of multiple independent data publications. A data owner publishes a dataset, which contains overlapping population with other datasets published by other independent data owners. In this paper we analyze the privacy risk in the such scenario and vulnerability of partitioned based anonymization methods. We show that no partitioned based anonymization methods can protect privacy in arbitrary data distributions, and identify a case that the privacy can be protected in the scenario. We propose a new generalization principle -cloning to protect privacy for multiple independent data publications. We also develop an effective algorithm to achieve the cloning. We experimentally show that the proposed algorithm anonymizes data to satisfy the privacy requirement and preserves good data utility.
|Item Type:||Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)|
|Additional Information:||Permanent restricted access to published version due to publisher copyright policy.|
|Uncontrolled Keywords:||security; integrity; protection|
|Depositing User:||Dr Hua Wang|
|Date Deposited:||20 Feb 2012 07:35|
|Last Modified:||03 Jul 2013 01:04|
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