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Journal of Intelligent Information Systems

Erschienen in:

24.06.2019

Safe disassociation of set-valued datasets

verfasst von: Nancy Awad, Bechara Al Bouna, Jean-Francois Couchot, Laurent Philippe

Erschienen in: Journal of Intelligent Information Systems | Ausgabe 3/2019

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Abstract

Disassociation is a bucketization based anonymization technique that divides a set-valued dataset into several clusters to hide the link between individuals and their complete set of items. It increases the utility of the anonymized dataset, but on the other side, it raises many privacy concerns, one in particular, is when the items are tightly coupled to form what is called, a cover problem. In this paper, we present safe disassociation, a technique that relies on partial suppression, to overcome the aforementioned privacy breach encountered when disassociating set-valued datasets. Safe disassociation allows the k^m-anonymity privacy constraint to be extended to a bucketized dataset and copes with the cover problem. We describe our algorithm that achieves the safe disassociation and we provide a set of experiments to demonstrate its efficiency.

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In what follows, we use k^m-disassociation to denote a dataset that is disassociated and satisfies k^m-anonymity.

Vertical partitioning creates k^m-anonymous record chunks.

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Barakat, S., al Bouna, B., Nassar, M., Guyeux, C. (2016). On the evaluation of the privacy breach in disassociated set-valued datasets. In Callegari, C., van Sinderen, M., Sarigiannidis, P.G., Samarati, P., Cabello, E., Lorenz, P., Obaidat, M.S. (Eds.) Proceedings of the 13th International Joint Conference on e-Business and Telecommunications (ICETE 2016) - Volume 4: SECRYPT, Lisbon, Portugal, July 26-28, 2016 (pp. 318–326). SciTePress.

Bewong, M., Liu, J., Liu, L., Li, J. (2017). Utility aware clustering for publishing transactional data. In Kim, J., Shim, K., Cao, L., Lee, J.-G., Lin, X., Moon, Y.-S. (Eds.) Advances in Knowledge Discovery and Data Mining (pp. 481–494). Cham: Springer International Publishing.CrossRef

Biskup, J., Marcel, P.B., Wiese, L. (2011). On the inference-proofness of database fragmentation satisfying confidentiality constraints. In: Proceedings of the 14th Information Security Conference, Xian, China.

Barbaro, M., & Zeller, T. (2006). A face is exposed for aol searcher no. 4417749.

Chen, L., Zhong, S., Wang, L.-E., Li, X. (2016). A sensitivity-adaptive ρ-uncertainty model for set-valued data. In International Conference on Financial Cryptography and Data Security 2016 (pp. 460–473). Berlin: Springer.

Ciriani, V., De Capitani Di Vimercati, S., Foresti, S., Jajodia, S., Paraboschi, S., Samarati, P. (2010). Combining fragmentation and encryption to protect privacy in data storage. ACM Transactions on Information and System Security, 13, 22:1–22:33.CrossRef

De Capitani di Vimercati, S, Foresti, S., Jajodia, S., Livraga, G., Paraboschi, S., Samarati, P. (2013). Extending loose associations to multiple fragments. In Proceedings of the 27th International Conference on Data and Applications Security and Privacy XXVII, DBSec’13 (pp. 1–16). Berlin: Springer.

Dwork, C., McSherry, F., Nissim, K., Smith, A. (2006). Calibrating noise to sensitivity in private data analysis. In Proceedings of the Third Conference on Theory of Cryptography, TCC’06 (pp. 265–284). Berlin: Springer.CrossRef

Fard, A.M., & Wang, K. (2010). An effective clustering approach to web query log anonymization. In: Proceedings of the 2010 International Conference on Security and Cryptography (SECRYPT) (pp. 1–11). IEEE.

He, Y., & Naughton, J.F. (2009). Anonymization of set-valued data via top-down, local generalization. Proceedings of the VLDB Endowment, 2(1), 934–945.CrossRef

Jia, X., Pan, C., Xu, X., Zhu, K.Q., Lo, E. (2014). ρ-uncertainty anonymization by partial suppression. In Bhowmick, S.S., Dyreson, C.E., Jensen, C.S., Lee, M.L., Muliantara, A., Thalheim, B. (Eds.) Database Systems for Advanced Applications, volume 8422 of Lecture Notes in Computer Science (pp. 188–202). Berlin: Springer International Publishing.

Loukides, G., Liagouris, J., Gkoulalas-Divanis, A., Terrovitis, M. (2015). Utility-constrained electronic health record data publishing through generalization and disassociation. In Gkoulalas-Divanis, A., & Loukides, G. (Eds.) Medical Data Privacy Handbook (pp. 149–177). Berlin: Springer International Publishing.

Loukides, G., Liagouris, J., Gkoulalas-divanis, A., Terrovitis, M. (2014). Disassociation for electronic health record privacy. Journal of Biomedical Informatics, 50, 46–61.CrossRef

Li, T., Li, N., Zhang, J., Molloy, I. (2012). Slicing: a new approach for privacy preserving data publishing. IEEE Transactions on Knowledge and Data Engineering, 24(3), 561–574.CrossRef

Machanavajjhala, A., Gehrke, J., Kifer, D., Venkitasubramaniam, M. (2006). l-diversity: Privacy beyond k-anonymity. In: Proceedings of the 22nd IEEE International Conference on Data Engineering (ICDE 2006), Atlanta Georgia.

Samarati, P. (2001). Protecting respondents’ identities in microdata release. IEEE Transactions on Knowledge and Data Engineering, 13(6), 1010–1027.CrossRef

Sweeney, L. (2002). k-anonymity: a model for protecting privacy. International Journal on Uncertainty, Fuzziness and Knowledge-based Systems, 10(5), 557–570.MathSciNetCrossRef

Terrovitis, M., Mamoulis, N., Kalnis, P. (2008). Privacy-preserving anonymization of set-valued data. PVLDB, 1(1), 115–125.

Terrovitis, M., Mamoulis, N., Liagouris, J., Skiadopoulos, S. (2012). Privacy preservation by disassociation. Proceedings of the VLDB Endowment, 5(10), 944–955.CrossRef

Wang, J., Deng, C., Li, X. (2018). Two privacy-preserving approaches for publishing transactional data streams. IEEE Access, pp. 1–1.

Ke, W., Wang, P., Fu, A.W., Wong, R.C.-W. (2016). Generalized bucketization scheme for flexible privacy settings. Information Sciences, 348, 377–393.MathSciNetCrossRef

Xiao, X., & Tao, Y. (2006). Anatomy: Simple and effective privacy preservation. In: Proceedings of 32nd International Conference on Very Large Data Bases (VLDB 2006), Seoul, Korea, September 12-15.

Zhang, H., Zhou, Z., Ye, L., Xiaojiang, D.U. (2015). Towards privacy preserving publishing of set-valued data on hybrid cloud. In: IEEE Transactions on cloud computing.

Titel: Safe disassociation of set-valued datasets
verfasst von: Nancy Awad
Bechara Al Bouna
Jean-Francois Couchot
Laurent Philippe
Publikationsdatum: 24.06.2019
Verlag: Springer US
Erschienen in: Journal of Intelligent Information Systems / Ausgabe 3/2019
Print ISSN: 0925-9902
Elektronische ISSN: 1573-7675
DOI: https://doi.org/10.1007/s10844-019-00568-7

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