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Jianneng Cao, Barbara Carminati, Elena Ferrari, KianLee Tan, "CASTLE: Continuously Anonymizing Data Streams," IEEE Transactions on Dependable and Secure Computing, vol. 8, no. 3, pp. 337352, May/June, 2011.  
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@article{ 10.1109/TDSC.2009.47, author = {Jianneng Cao and Barbara Carminati and Elena Ferrari and KianLee Tan}, title = {CASTLE: Continuously Anonymizing Data Streams}, journal ={IEEE Transactions on Dependable and Secure Computing}, volume = {8}, number = {3}, issn = {15455971}, year = {2011}, pages = {337352}, doi = {http://doi.ieeecomputersociety.org/10.1109/TDSC.2009.47}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
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TY  JOUR JO  IEEE Transactions on Dependable and Secure Computing TI  CASTLE: Continuously Anonymizing Data Streams IS  3 SN  15455971 SP337 EP352 EPD  337352 A1  Jianneng Cao, A1  Barbara Carminati, A1  Elena Ferrari, A1  KianLee Tan, PY  2011 KW  Data stream KW  privacypreserving data mining KW  anonymity. VL  8 JA  IEEE Transactions on Dependable and Secure Computing ER   
[1] R. Agrawal and R. Srikant, "Fast Algorithms for Mining Association Rules in Large Databases," Proc. Int'l Conf. Very Large Databases (VLDB), pp. 478499, 1994.
[2] R. Agrawal and R. Srikant, "PrivacyPreserving Data Mining," Proc. SIGMOD, pp. 439450, 2000.
[3] C.C. Aggarwal, "On $k$ Anonymity and the Curse of Dimensionality," Proc. Int'l Conf. Very Large Databases (VLDB), pp. 901909, 2005.
[4] C.C. Aggarwal, J. Han, J. Wang, and P.S. Yu, "A Framework for Clustering Evolving Data Streams," Proc. Int'l Conf. Very Large Databases (VLDB), pp. 8192, 2003.
[5] C.C. Aggarwal and P.S. Yu, "A Condensation Approach to Privacy Preserving Data Mining," Proc. Int'l Conf. Extending Database Technology (EDBT), pp. 183199, 2004.
[6] G. Aggarwal, T. Feder, K. Kenthapadi, S. Khuller, R. Panigrahy, D. Thomas, and A. Zhu, "Achieving Anonymity via Clustering," Proc. Symp. Principles of Database Systems (PODS), pp. 153162, 2006.
[7] M. Atzori, "Weak $k$ Anonymity: A LowDistortion Model for Protecting Privacy," Proc. Int'l Security Conf., pp. 6071, 2006.
[8] R.J. Bayardo and R. Agrawal, "Data Privacy through Optimal $k$ Anonymization," Proc. Int'l Conf. Data Eng. (ICDE), pp. 217228, 2005.
[9] J.W. Byun, Y. Sohn, E. Bertino, and N. Li, "Secure Anonymization for Incremental Data Sets," Proc. Very Large Databases (VLDB) Workshop Secure Data Management, pp. 4863, 2006.
[10] J.W. Byun, A. Kamra, E. Bertino, and N. Li, "Efficient $k$ Anonymization Using Clustering Techniques," Proc. Database Systems for Advanced Applications (DASFAA), pp. 188200, 2007.
[11] J. Cao, B. Carminati, E. Ferrari, and K.L. Tan, "CASTLE: A DelayConstrained Scheme for $k\_s$ Anonymizing Data Streams," Proc. Int'l Conf. Data Eng. (ICDE), Poster Paper, pp. 13761378, 2008.
[12] P. Domingos and G. Hulten, "Mining HighSpeed Data Streams," Proc. Int'l Conf. Knowledge Discovery and Data Mining (KDD), pp. 7180, 2000.
[13] P. Zhang, X. Zhu, and Y. Shi, "Categorizing and Mining Concept Drifting Data Streams," Proc. Int'l Conf. Knowledge Discovery and Data Mining (KDD), pp. 812820, 2008.
[14] C. Luo, H. Thakkar, H. Wang, and C. Zaniolo, "A Native Extension of SQL for Mining Data Streams," Proc. SIGMOD, pp. 873875, 2005.
[15] J. DomingoFerrer and V. Torra, "Ordinal, Continuous and Heterogeneous $k$ Anonymity through Microaggregation," Data Mining and Knowledge Discovery, vol. 11, no. 2, pp. 195212, 2005.
[16] J. DomingoFerrer, F. Sebe, and A. Solanas, "A PolynomialTime Approximation to Optimal Multivariate Microaggregation," Computers and Math. with Applications, vol. 55, no. 4, pp. 714732, 2008.
[17] S. Guha, N. Mishra, R. Motwani, and L. O'Callaghan, "Clustering Data Streams," Proc. IEEE Symp. Foundations of Computer Science (FOCS), pp. 359366, 2000.
[18] B.C.M. Fung, K. Wang, and P.S. Yu, "TopDown Specialization for Information and Privacy Preservation," Proc. Int'l Conf. Data Eng. (ICDE), pp. 205216, 2005.
[19] V.S. Iyengar, "Transforming Data to Satisfy Privacy Constraints," Proc. Int'l Conf. Knowledge Discovery and Data Mining (KDD), pp. 279288, 2002.
[20] S. Kim and W. Winkler, "Masking Microdata Files," Proc. Section on Survey Research Methods, pp. 114119, 1995.
[21] K. LeFevre, D.J. DeWitt, and R. Ramakrishnan, "Incognito: Efficient FullDomain $k$ Anonymity," Proc. SIGMOD, pp. 4960, 2005.
[22] K. LeFevre, D.J. DeWitt, and R. Ramakrishnan, "Mondrian Multidimensional KAnonymity," Proc. Int'l Conf. Data Eng. (ICDE), p. 25, 2006.
[23] N. Li and T. Li, "$t$ Closeness: Privacy beyond $k$ Anonymity and $\ell$ Diversity," Proc. Int'l Conf. Data Eng. (ICDE), pp. 106115, 2007.
[24] A. Machanavajjhala, J. Gehrke, D. Kifer, and M. Venkitasubramaniam, "LDiversity: Privacy beyond $k$ Anonymity," Proc. Int'l Conf. Data Eng. (ICDE), p. 24, 2006.
[25] P. Samarati and L. Sweeney, "Generalizing Data to Provide Anonymity When Disclosing Information," Proc. Symp. Principles of Database Systems (PODS), p. 188, 1998.
[26] J. Pei, J. Xu, Z. Wang, W. Wang, and K. Wang, "Maintaining KAnonymity against Incremental Updates," Proc. Int'l Conf. Scientific and Statistical Database Management (SSDBM), p. 5, 2007.
[27] L. Qiu, Y. Li, and X. Wu, "Protecting Business Intelligence and Customer Privacy While Outsourcing Data Mining Tasks," Knowledge and Information Systems, vol. 17, no. 1, pp. 99120, 2008.
[28] L. Sweeney, "Achieving $k$ Anonymity Privacy Protection Using Generalization and Suppression," Int'l J. Uncertainty, Fuzziness, and KnowledgeBased Systems, vol. 10, pp. 571588, 2002.
[29] T.M. Truta and A. Campan, "$k$ Anonymization Incremental Maintenance and Optimization Techniques," Proc. ACM Symp. Applied Computing (SAC), pp. 380387, 2007.
[30] X. Xiao and Y. Tao, "MInvariance: Towards Privacy Preserving RePublication of Dynamic Data Sets," Proc. SIGMOD, pp. 689700, 2007.
[31] M. Laszlo and S. Mukherjee, "Approximation Bounds for Minimum Information Loss Microaggregation," IEEE Trans. Knowledge and Data Eng., vol. 21, no. 11, pp. 16431647, Nov. 2009.
[32] G. Ghinita, P. Karras, P. Kalnis, and N. Mamoulis, "Fast Data Anonymization with Low Information Loss," Proc. Int'l Conf. Very Large Databases (VLDB), pp. 758769, 2007.