Multirelational k-Anonymity

Warning The system is temporarily closed to updates for reporting purpose.

Nergiz, Mehmet Ercan and Clifton, Christopher and Nergiz, Ahmet Erhan (2009) Multirelational k-Anonymity. IEEE Transactions On Knowledge and Data Engineering, 21 (8). pp. 1104-1117. ISSN 1041-4347

Full text not available from this repository.

Official URL: http://dx.doi.org/10.1109/TKDE.2008.210


k-Anonymity protects privacy by ensuring that data cannot be linked to a single individual. In a k-anonymous data set, any identifying information occurs in at least k tuples. Much research has been done to modify a single-table data set to satisfy anonymity constraints. This paper extends the definitions of k-anonymity to multiple relations and shows that previously proposed methodologies either fail to protect privacy or overly reduce the utility of the data in a multiple relation setting. We also propose two new clustering algorithms to achieve multirelational anonymity. Experiments show the effectiveness of the approach in terms of utility and efficiency.

Item Type:Article
Uncontrolled Keywords:Privacy; relational database; security; integrity; protection
Subjects:Q Science > QA Mathematics > QA075 Electronic computers. Computer science
ID Code:13135
Deposited By:Mehmet Ercan Nergiz
Deposited On:03 Dec 2009 09:59
Last Modified:24 Jul 2019 09:46

Repository Staff Only: item control page