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Privacy-Preserving Updates to Generalization-Based K-Anonymous and Confidential Database

D. Radha

Abstract


In this paper, two protocols are proposed for solving the problem on suppression-based and generalization-based k-anonymous and confidential databases. The protocols rely on well-known cryptographic assumptions. Let us begin the explanation with an example. Suppose Alice owns a k-anonymous database and needs to determine whether her database, when inserted with a tuple owned by Bob, is still k-anonymous. Also, suppose that access to the database is strictly controlled, because for example data are used for certain experiments that need to be maintained confidential.  Clearly, allowing Alice to directly read the contents of the tuple breaks the privacy of Bob (e.g., a patient’s medical record); on the other hand, the confidentiality of the database managed by Alice is violated once Bob has access to the contents of the database. Thus, the problem  is to check whether the database inserted with the  tuple  is still k-anonymous, without  letting  Alice and  Bob  know  the  contents of the  tuple  and  the  database  respectively. The project is designed by using Microsoft Visual C#. NET 2005 as a front end and MS SQL SERVER 2005 as a back end

Keywords


Privacy, Anonymity, Data Management, Secure Computation.

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References


Aggarwal.G, Feder.T, Kenthapadi.K, Motwani.R, Panigrahy, Thomas.D, Zhu.A. “Anonymizing Tables”, Proc.Int’l Conf. Database Theory (ICDT), UK, 2005.

Agarwal.R, Evfimievski.A, Srikant.R. “Information sharing across Private Databases”, in Proc. Of ACM SIGMOD Int’l Con Management of Data, San Diego, California, USA, 2003.

Bertino.E, Sandhu.R. “Database Security- Concepts, Approaches and Challenges”, IEEE Transactions on Dependable and Secure Computing, vol2, no.1,pp.2-19, 2005.

Boneh.D, Crescenzo.G, Ostrowsky.R, Persiano.G. “ Public Key Encryption with Keyword Search”, Proc. Eurocrypt Conf, 2004.

Canetti.R, Ishai.Y, Kumar.R, Reiter.M.K, Rubinfeld.R, Wright.R.N. “ Selective Private Function Evaluation with Application to Private Statistics”, Proc. ACM Symp. Principles of Distributed Computing (PODC), 2001.


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