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A Dynamic Programming Approach for Privacy Preserving Collaborative Data Publishing
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 22 - Number 4 |
| Year of Publication: 2011 |
| Authors: S.Ram Prasad Reddy, KVSVN Raju, V.Valli Kumari |
10.5120/2572-3542
|
S.Ram Prasad Reddy, KVSVN Raju, V.Valli Kumari . A Dynamic Programming Approach for Privacy Preserving Collaborative Data Publishing. International Journal of Computer Applications. 22, 4 ( May 2011), 18-23. DOI=10.5120/2572-3542
Abstract
Organizations share their data about customers for exploring potential business avenues. The sharing of data has posed several threats leading to individual identification. Owing to this, privacy preserving data publication has become an important research problem. The main goals of this problem are to preserve privacy of individuals while revealing useful information. An organization may implement and follow its privacy policy. But when two companies share information about a common set of individuals, and if their privacy policies differ, it is likely that there is privacy breach unless there is a common policy. One such solution was proposed for such a scenario, based on k-anonymity and cut-tree method for 2-party data. This paper suggests a simple solution for integrating n-party data using dynamic programming on subsets. The solution is based on thresholds for privacy and informativeness based on k-anonymity.
References
- Oliveira, S.R.M., Zaiane, O.R.: Privacy preservation when sharing data for clustering. In: Proc. Workshop on Secure Data Management in a Connected World, 2004.
- Centers for Medicare & Medicaid Services. The Health Insurance Portability and Accountability Act of 1996 (HIPAA). Online at http://www.cms.hhs.gov/hipaa/, 1996.
- Council Directive (EC) 2001/29/EC of 22 May 2001 on the harmonization of certain aspects of copyright and related rights in the information society.
- L. Sweeny. : k-anonymity: a model for protecting privacy. International Journal on Uncertainty, Fuzziness and Knowledge-based Systems,2002.
- K. Wang, P. S. Yu, and S. Chakraborty. : Bottom-up generalization: A data mining Solution to privacy protection. In ICDM, 2004.
- K. Wang, B. C. M. Fung, and P. S. Yu. Template-based privacy preservation in classification problems. In IEEE ICDM, November 2005.
- R. Agrawal and R. Srikant. : Privacy-Preserving Data Mining. In Proceedings of the ACM SIGMOD International Conference on Management of Data, Dallas, Texas, May 2000.
- Dalenius, T.: Finding a needle in a haystack - or identifying anonymous census record. Journal of Official Statistics, 1986.
- Sweeney, L.: Achieving k-anonymity privacy protection using generalization andsuppression. International Journal on Uncertainty, Fuzziness, and Knowledge-based Systems, 2002.
- Hundepool, A., Willenborg, L.: µ- and τ-argus: Software for statistical disclosurecontrol. In: Third International Seminar on Statistical Confidentiality, Bled, 1996.
- Agrawal, R., Evfimievski, A., Srikant, R.: Information sharing across privatedatabases. In: Proceedings of theACM SIGMOD International Conference on Management of Data, San Diego, California, 2003.
- Yao, A.C.: Protocols for secure computations. In: Proceedings of the 23rd Annual IEEE Symposium on Foundations of Computer Science, 1982.
- Liang, G., Chawathe, S.S.: Privacy-preserving inter-database operations. In: Proceedings of the 2nd Symposium on
- K. Wang, B. C. M. Fung, and G. Dong. : Integrating private databases for data analysis. In IEEE ISI, May 2005.
- Jiang, W. and Clifton, C. : Privacy-preserving distributed k-anonymity. In Proceedings of the 19thAnnual IFIP WG 11.3 Working Conference on Data and Applications Security, 2005.
- Jiang, W. and Clifton, C. : A secure distributed framework for achieving k-anonymity. Very LargeData Bases, 2006.
- Pawel Jurczyk and Li Xiong. : Distributed Anonymization: Achieving Privacy for Both Data Subjects and Data Providers, Atlanta GA 30322, USA.
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