The Community for Technology Leaders
RSS Icon
Issue No.02 - Feb. (2013 vol.25)
pp: 311-324
Tamir Tassa , The Open University, Ra'anana, Israel
Dror J. Cohen , The Open University, Ra'anana, Israel
We study the problem of privacy-preservation in social networks. We consider the distributed setting in which the network data is split between several data holders. The goal is to arrive at an anonymized view of the unified network without revealing to any of the data holders information about links between nodes that are controlled by other data holders. To that end, we start with the centralized setting and offer two variants of an anonymization algorithm which is based on sequential clustering (Sq). Our algorithms significantly outperform the SaNGreeA algorithm due to Campan and Truta which is the leading algorithm for achieving anonymity in networks by means of clustering. We then devise secure distributed versions of our algorithms. To the best of our knowledge, this is the first study of privacy preservation in distributed social networks. We conclude by outlining future research proposals in that direction.
Clustering algorithms, Social network services, Loss measurement, Tin, Algorithm design and analysis, Partitioning algorithms, distributed computation, Social networks, clustering, privacy preserving data mining
Tamir Tassa, Dror J. Cohen, "Anonymization of Centralized and Distributed Social Networks by Sequential Clustering", IEEE Transactions on Knowledge & Data Engineering, vol.25, no. 2, pp. 311-324, Feb. 2013, doi:10.1109/TKDE.2011.232
[1] G. Aggarwal, T. Feder, K. Kenthapadi, R. Motwani, R. Panigrahy, D. Thomas, and A. Zhu, "Anonymizing Tables," Proc. 10th Int'l Conf Database Theory (ICDT), vol. 3363, pp. 246-258, 2005.
[2] L. Backstrom, C. Dwork, and J.M. Kleinberg, "Wherefore Art Thou r3579x?: Anonymized Social Networks, Hidden Patterns, and Structural Steganography," Proc. 16th Int'l Conf. World Wide Web (WWW), pp. 181-190, 2007.
[3] A. Barabási and R. Albert, "Emergence of Scaling in Random Networks," Science, vol. 286, pp. 509-512, 1999.
[4] J. Benaloh, "Secret Sharing Homomorphisms: Keeping Shares of a Secret Secret," Proc. Advances in Cryptology (Crypto), pp. 251-260, 1986.
[5] F. Bonchi, A. Gionis, and T. Tassa, "Identity Obfuscation in Graphs Through the Information Theoretic Lens," Proc. IEEE 27th Int'l Conf. Data Eng. (ICDE), pp. 924-935, 2011.
[6] A. Campan and T.M. Truta, "Data and Structural $k$ -Anonymity in Social Networks," Proc. Second ACM SIGKDD Int'l Workshop Privacy, Security, and Trust in KDD (PinKDD), pp. 33-54, 2008.
[7] J. Goldberger and T. Tassa, "Efficient Anonymizations with Enhanced Utility," Trans. Data Privacy, vol. 3, pp. 149-175, 2010.
[8] S. Hanhijärvi, G. Garriga, and K. Puolamaki, "Randomization Techniques for Graphs," Proc. Ninth SIAM Int'l Conf. Data Mining (SDM), pp. 780-791, 2009.
[9] M. Hay, G. Miklau, D. Jensen, D.F. Towsley, and P. Weis, "Resisting Structural Re-Identification in Anonymized Social Networks," Proc. VLDB Endowment (PVLDB), vol. 1, pp. 102-114, 2008.
[10] M. Hay, G. Miklau, D. Jensen, P. Weis, and S. Srivastava, "Anonymizing Social Networks," Univ. of Massachusetts, technical report, vol. 7, no. 19, 2007.
[11] V. Iyengar, "Transforming Data to Satisfy Privacy Constraints," Proc. Eighth ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining (KDD), pp. 279-288, 2002.
[12] W. Jiang and C. Clifton, "A Secure Distributed Framework for Achieving k-Anonymity," The Int'l J. Very Large Data Bases, vol. 15, pp. 316-333, 2006.
[13] M. Kantarcioglu and C. Clifton, "Privacy-Preserving Distributed Mining of Association Rules on Horizontally Partitioned Data," IEEE Trans. Knowledge and Data Eng., vol. 16, no. 9, pp. 1026-1037, Sept. 2004.
[14] S. Kirkpatrick, D.G. Jr, and M.P. Vecchi, "Optimization by Simmulated Annealing," Science, vol. 220, no. 4598, pp. 671-680, 1983.
[15] K. Liu and E. Terzi, "Towards Identity Anonymization on Graphs," Proc. ACM SIGMOD Int'l Conf. Management of Data (SIGMOD), pp. 93-106, 2008.
[16] A. Machanavajjhala, D. Kifer, J. Gehrke, and M. Venkitasubramaniam, "$\ell$ -Diversity: Privacy Beyond k-Anonymity," ACM Trans. Knowledge Discovery and Data, vol. 1, no. 1,article 3, 2007.
[17] M.E. Nergiz and C. Clifton, "Thoughts on $k$ -Anonymization," Proc. Int'l Conf. Data Eng. (ICDE), p. 96, 2006.
[18] A. Schuster, R. Wolff, and B. Gilburd, "Privacy-Preserving Association Rule Mining in Large-Scale Distributed Systems," Proc. IEEE Int'l Symp. Cluster Computing and the Grid (CCGRID), pp. 411-418, 2004.
[19] N. Slonim, N. Friedman, and N. Tishby, "Unsupervised Document Classification Using Sequential Information Maximization," Proc. 25th Ann. Int'l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR), pp. 129-136, 2002.
[20] L. Sweeney, "Uniqueness of Simple Demographics in the U.S. Population," Laboratory for Int'l Data Privacy (LIDAP-WP4), 2000.
[21] J. Vaidya and C. Clifton, "Privacy Preserving Association Rule Mining in Vertically Partitioned Data," Proc. ACM SIGKDD Eighth Int'l Conf. Knowledge Discovery and Data Mining (KDD), pp. 639-644, 2002.
[22] D. Watts and S. Strogatz, "Collective Dynamics of 'Small-World' Networks," Nature, vol. 393, pp. 409-410, 1998.
[23] W. Wu, Y. Xiao, W. Wang, Z. He, and Z. Wang, "$k$ -Symmetry Model for Identity Anonymization in Social Networks," Proc. 13th Int'l Conf. Extending Database Technology (EDBT), pp. 111-122, 2010.
[24] X. Wu, X. Ying, K. Liu, and L. Chen, "A Survey of Privacy-Preservation of Graphs and Social Networks," Managing and Mining Graph Data, C. Aggarwal and H. Wang, eds., first ed., chapter 14. Springer-Verlag, 2010.
[25] A. Yao, "Protocols for Secure Computation," Proc. Symp. Foundations of Computer Science (FOCS), pp. 160-164, 1982.
[26] X. Ying and X. Wu, "Randomizing Social Networks: A Spectrum Preserving Approach," Proc. SIAM Conf. Data Mining (SDM), pp. 739-750, 2008.
[27] X. Ying and X. Wu, "Graph Generation with Prescribed Feature Constraints," Proc. SIAM Conf. Data Mining (SDM), pp. 966-977, 2009.
[28] X. Ying and X. Wu, "On Link Privacy in Randomizing Social Networks," Proc. 13th Pacific-Asia Conf. Advances in Knowledge Discovery and Data Mining (PAKDD), pp. 28-39, 2009.
[29] E. Zheleva and L. Getoor, "Preserving the Privacy of Sensitive Relationship in Graph Data," Proc. ACM SIGKDD First Int'l Conf. Privacy, Security, and Trust in KDD (PinKDD), pp. 153-171, 2007.
[30] S. Zhong, Z. Yang, and R. Wright, "Privacy-Enhancing $k$ -Anonymization of Customer Data," Proc. 24th ACM SIGMOD-SIGACT-SIGART Symp. Principles of Database Systems (PODS), pp. 139-147, 2005.
[31] B. Zhou and J. Pei, "Preserving Privacy in Social Networks against Neighborhood Attacks," Proc. IEEE 24th Int'l Conf. Data Eng. (ICDE), pp. 506-515, 2008.
7 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool