Anonymous publication of sensitive transactional data

IEEE Transactions on Knowledge and Data Engineering

Volumn 23, Issue 2, 2011, Pages 161-174

  Ghinita, Gabriel ^a   Kalnis, Panos ^b   Tao, Yufei ^c  

^a Purdue University   (United States)

^b KING ABDULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Saudi Arabia)

^c CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

anonymity; Privacy; transactional data

Indexed keywords

ANONYMITY; ANONYMIZATION; BAND MATRIX; COMPUTATIONAL OVERHEADS; DATA PUBLISHING; DATA TRANSFORMATION; DATA UTILITIES; EXECUTION TIME; EXISTING METHOD; GRAY CODES; GRAY ENCODING; HIGH DIMENSIONAL DATA; HIGH DIMENSIONAL SPACES; INFORMATION LOSS; K-ANONYMITY; LOCALITY SENSITIVE HASHING; LOW DIMENSIONALITY; NEAREST-NEIGHBORS; PRIVACY; PRIVACY PRESERVING; REAL LIFE DATASETS; RELATIONAL DATA; STATE OF THE ART; TRANSACTIONAL DATA;

LINEAR TRANSFORMATIONS; METADATA; SORTING;

DATA PRIVACY;

EID: 78650584378     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2010.101     Document Type: Article

References (29)

1. G. Ghinita, Y. Tao, and P. Kalnis, "On the Anonymization of Sparse, High-Dimensional Data," Proc. IEEE Int'l Conf. Data Eng. (ICDE), pp. 715-724, 2008.
2. A. Machanavajjhala, J. Gehrke, D. Kifer, and M. Venkitasubrama-niam, "l-Diversity: Privacy beyond k-Anonymity," Proc. IEEE Int'l Conf. Data Eng. (ICDE), 2006.
3. K. LeFevre, D.J. DeWitt, and R. Ramakrishnan, "Incognito: Efficient Full-Domain k-Anonymity," Proc. ACM SIGMOD, pp. 49-60, 2005.
4. K. LeFevre, D.J. DeWitt, and R. Ramakrishnan, "Mondrian Multidimensional k-Anonymity," Proc. IEEE Int'l Conf. Data Eng. (ICDE), 2006.
5. C.C. Aggarwal, "On k-Anonymity and the Curse of Dimensionality, " Proc. Int'l Conf. Very Large Data Bases (VLDB), pp. 901-909, 2005.
6. X. Xiao and Y. Tao, "Anatomy: Simple and Effective Privacy Preservation," Proc. Int'l Conf. Very Large Data Bases (VLDB), pp. 139-150, 2006.
7. A. Gionis, P. Indyk, and R. Motwani, "Similarity Search in High Dimensions via Hashing," Proc. Int'l Conf. Very Large Data Bases (VLDB), pp. 518-529, 1999.
8. S. Skiena, Implementing Discrete Mathematics: Combinatorics and Graph Theory with Mathematica. Addison-Wesley, 1990.
9. B.-C. Chen, K. LeFevre, and R. Ramakrishnan, "Privacy Skyline: Privacy with Multidimensional Adversarial Knowledge," Proc. Int'l Conf. Very Large Data Bases (VLDB), pp. 770-781, 2007.
10. R. Agrawal and R. Srikant, "Privacy Preserving Data Mining," Proc. ACM SIGMOD, pp. 439-450, 2000.
11. Z. Huang, W. Du, and B. Chen, "Deriving Private Information from Randomized Data," Proc. ACM SIGMOD, pp. 37-48, 2005.
12. K. LeFevre, D.J. DeWitt, and R. Ramakrishnan, "Workload-Aware Anonymization," Proc. Int'l Conf. Knowledge Discovery and Data Mining (KDD), pp. 277-286, 2006.
13. P. Samarati, "Protecting Respondents' Identities in Microdata Release," IEEE Trans. Knowledge and Data Eng., vol. 13, no. 6, pp. 1010-1027, Nov./Dec. 2001.
14. G. Aggarwal, T. Feder, K. Kenthapadi, S. Khuller, R. Panigrahy, D. Thomas, and A. Zhu, "Achieving Anonymity via Clustering," Proc. ACM Symp. Principles of Database Systems (PODS), pp. 153-162, 2006.
15. G. Ghinita, P. Karras, P. Kalnis, and N. Mamoulis, "Fast Data Anonymization with Low Information Loss," Proc. Int'l Conf. Very Large Data Bases (VLDB), pp. 758-769, 2007.
16. Q. Zhang, N. Koudas, D. Srivastava, and T. Yu, "Aggregate Query Answering on Anonymized Tables," Proc. IEEE Int'l Conf. Data Eng. (ICDE), pp. 116-125, 2007.
17. M. Atzori, F. Bonchi, F. Giannotti, and D. Pedreschi, "Anonymity Preserving Pattern Discovery," VLDB J., vol. 17, pp. 703-727, 2008.
18. V. Verykios, A. Elmagarmid, E. Bertino, Y. Saygin, and E. Dasseni, "Association Rule Hiding," IEEE Trans. Knowledge and Data Eng., vol. 16, no. 4, pp. 434-447, Apr. 2004.
19. C.C. Aggarwal and P.S. Yu, "On Privacy-Preservation of Text and Sparse Binary Data with Sketches," Proc. SIAM Conf. Data Mining, 2007.
20. M. Terrovitis, N. Mamoulis, and P. Kalnis, "Privacy-Preserving Anonymization of Set-Valued Data," Proc. Int'l Conf. Very Large Data Bases (VLDB), 2008.
21. Y. Xu, K. Wang, A.W.-C. Fu, and P.S. Yu, "Anonymizing Transaction Databases for Publication," Proc. SIGKDD, pp. 767-775, 2008.
22. D. Richards, "Data Compression and Gray-Code Sorting," Information Processing Letters, vol. 22, pp. 201-205, 1986.
23. A. Pinar, T. Tao, and H. Ferhatosmanoglu, "Compressing Bitmap Indices by Data Reorganization," Proc. IEEE Int'l Conf. Data Eng. (ICDE), pp. 310-321, 2005.
24. D. Kifer and J. Gehrke, "Injecting Utility into Anonymized Datasets," Proc. ACM SIGMOD, pp. 217-228, 2006.
25. A. Andoni, M. Datar, N. Immorlica, P. Indyk, and V. Mirrokni, Nearest Neighbor Methods in Learning and Vision: Theory and Practice. MIT Press, 2006.
26. J.K. Reid and J.A. Scott, "Reducing the Total Bandwidth of a Sparse Unsymmetric Matrix," SIAM J. Matrix Analysis and Applications, vol. 28, no. 3, pp. 805-821, 2006.
27. C. Papadimitriou, "The NP-Completeness of the Bandwidth Minimization Problem," Computing, vol. 16, pp. 263-270, 1976.
28. Z. Zheng, R. Kohavi, and L. Mason, "Real World Performance of Association Rule Algorithms," Proc. Int'l Conf. Knowledge Discovery and Data Mining (KDD), pp. 401-406, 2001.
29. A. Narayanan and V. Shmatikov, "How to Break Anonymity of the Netflix Prize Dataset," http://arxiv.org/abs/cs/0610105, 2010.