Privacy-preserving data mashup

Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology, EDBT'09

Volumn , Issue , 2009, Pages 228-239

  Mohammed, Noman ^a   Fung, Benjamin C M ^a   Wang, Ke ^b   Hung, Patrick C K ^c  

^a Concordia University ^*  (Canada)

^b SIMON FRASER UNIVERSITY   (Canada)

^c UNIVERSITY OF ONTARIO INSTITUTE OF TECHNOLOGY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION ANALYSIS; CUSTOMIZABLE; DATA EXPLORATION; DATA MINING TASKS; FINANCIAL INDUSTRY; INTEGRATED DATA; PRIVACY PRESERVING; PRIVACY PROBLEMS; PRIVATE DATA; REAL LIFE DATA; SENSITIVE INFORMATIONS; WEB APPLICATION; WEB TECHNOLOGIES;

DATA HANDLING; DATA MINING; DATABASE SYSTEMS;

DATA PRIVACY;

EID: 70349096680     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1516360.1516388     Document Type: Conference Paper

References (46)

1. J. M. Abowd and J. Lane. New approaches to confidentiality protection: Synthetic data, remote access and research data centers. In Proc. of Privacy in Statistical Databases: CASC Project International Workshop (PSD 2004), pages 282-289, Barcelona, Spain, June 2004.
2. R. Agrawal, A. Evfimievski, and R. Srikant. Information sharing across private databases. In Proc. of the 2003 ACM SIGMOD, 2003.
3. R. Agrawal and R. Srikant. Privacy preserving data mining. In Proc. of the 2000 ACM SIGMOD, pages 439-450, Dallas, Texas, May 2000.
4. R. J. Bayardo and R. Agrawal. Data privacy through optimal k-anonymization. In Proc. of the 21st IEEE ICDE, pages 217-228, Tokyo, Japan, 2005.
5. C. Clifton, M. Kantarcioglu, J. Vaidya, X. Lin, and M. Y. Zhu. Tools for privacy preserving data mining. SIGKDD Explorations, 4(2), December 2002.
6. U. Dayal and H. Y. Hwang. View definition and generalization for database integration in a multidatabase systems. IEEE Transactions on Software Engineering, 10(6):628-645, 1984.
7. W. Du, Y. S. Han, and S. Chen. Privacy-preserving multivariate statistical analysis: Linear regression and classification. In Proc. of the 4th SDM, Florida, 2004.
8. W. Du and Z. Zhan. Building decision tree classifier on private data. In Workshop on Privacy, Security, and Data Mining at the IEEE ICDM, 2002.
9. C. Farkas and S. Jajodia. The inference problem: A survey. ACM SIGKDD Explorations Newsletter, 4(2):6-ll, 2003.
10. W. A. Fuller. Masking procedures for microdata disclosure limitation. Official Statistics, 9(2):383-406, 1993.
11. B. C. M. Fung, K. Wang, A. W. C. Fu, and J. Pei. Anonymity for continuous data publishing. In Proc. of the 11th EDBT, Nantes, France, March 2008.
12. B. C. M. Fung, K. Wang, and P. S. Yu. Top-down specialization for information and privacy preservation. In Proc. of the 21st IEEE ICDE, Tokyo, Japan, April 2005.
13. B. C. M. Fung, K. Wang, and P. S. Yu. Anonymizing classification data for privacy preservation. IEEE Transactions on Knowledge and Data Engineering (TKDE), 19(5):711-725, May 2007.
14. J. Goguen and J. Meseguer. Unwinding and inference control. In Proc. of the IEEE Symposium on Security and Privacy, Oakland, CA, 1984.
15. T. Hinke. Inference aggregation detection in database management systems. In Proc. of the IEEE Symposium, on Security and Privacy, pages 96-107, Oakland, CA, April 1988.
16. T. Hinke, H. Degulach, and A. Chandrasekhar. A fast algorithm for detecting second paths in database inference analysis. Journal of Computer Security, 1995.
17. R. D. Hof. Mix, match, and mutate. Business Week, July 2005.
18. A. Hundepool and L. Willenborg. μ- and τ-argus: Software for statistical disclosure control. In Proc. of the 3rd International Seminar on Statistical Confidentiality, 1996.
19. V. S. Iyengar. Transforming data to satisfy privacy constraints. In Proc. of the 8th A CM SIGKDD, pages 279-288, Edmonton, AB, Canada, July 2002.
20. S. Jajodia and C. Meadows. Inference problems in multilevel database management systems. IEEE Information Security: An Integrated Collection of Essays, pages 570-584, 1995.
21. W. Jiang and C. Clifton. Privacy-preserving distributed fc-anonymity. In Proc. of the 19th Annual IFIP WG 11.3 Working Conference on Data, and Applications Security, pages 166-177, August 2005.
22. W. Jiang and C. Clifton. A secure distributed framework for achieving fc-anonymity. Very Large Data Bases Journal (VLDBJ), 15(4):316-333, November 2006.
23. J. Kim and W. Winkler. Masking microdata files. In Proc. of the Section on Survey Research Methods, pages 114-119, 1995.
24. K. LeFevre, D. J. DeWitt, and R. Ramakrishnan. Workload-aware anonymization. In Proc. of the 12th ACM SIGKDD, Philadelphia, PA, August 2006.
25. A. Machanavajjhala, D. Kifer, J. Gehrke, and M. Venkitasubramaniam. ℓ-diversity: Privacy beyond k-anonymity. ACM TKDD, 1(1), March 2007.
26. J. M. Mateo-Sanz, A. Martínez-Ballesté, and J. Domingo-Ferrer. Fast generation of accurate synthetic microdata. In Proceedings of Privacy in Statistical Databases: CASC Project International Workshop (PSD 2004), pages 298-306, Barcelona, Spain, June 2004.
27. G. Miklau and D. Suciu. A formal analysis of information disclosure in data exchange. In Proc. of ACM SIGMOD, pages 575-586, Paris, France, 2004.
28. D. J. Newman, S. Hettich, C. L. Blake, and C. J. Merz. UCI repository of machine learning databases, 1998. http://ics.uci.edu/~mlearn/MLRepository.htrnl.
29. N. Nisan. Algorithms for selfish agents. In Proceedings of the 16th Symposium on Theoretical Aspects of Computer Science, Trier, Germany, March 1999.
30. S. Pohlig and M. Hellman. An improved algorithm for computing logarithms over gf(p) and its cryptographic significance. IEEE Transactions on Information Theory, IT-24:106-110, 1978.
31. J. R. Quinlan. CJh5: Programs for Machine Learning. Morgan Kaufmann, 1993.
32. P. Samarati. Protecting respondents' identities in microdata release. IEEE Transactions on Knowledge Engineering, 13(6):1010-1027, 2001.
33. P. Samarati and L. Sweeney. Generalizing data to provide anonymity when disclosing information. In Proc. of the 17th ACM PODS, 1998.
34. L. Sweeney. Achieving k-anonymity privacy protection using generalization and suppression. International Journal on Uncertainty, Fuzziness, and, Knowledge-based Systems, 10(5):571-588, 2002.
35. J. Vaidya and C. Clifton. Privacy preserving association rule mining in vertically partitioned data. In Proc. of the 8th ACM SIGKDD, pages 639-644, Edmonton, AB, Canada, 2002.
36. J. Vaidya and C. Clifton. Privacy-preserving k-means clustering over vertically partitioned data. In Proc. of the 9th ACM SIGKDD, pages 206-215, 2003.
37. K. Wang and B. C. M. Fung. Anonymizing sequential releases. In Proc. of the 12th ACM SIGKDD, pages 414-423, Philadelphia, PA, August 2006.
38. K. Wang, B. C. M. Fung, and P. S. Yu. Handicapping attacker's confidence: An alternative to k-anonymization. KAIS, ll(3):345-368, April 2007.
39. G. Wiederhold. Intelligent integration of information. In Proc. of the 1993 ACM SIGMOD, 1993.
40. R. C. W. Wong, J. Li., A. W. C. Fu, and K. Wang. (α, k)-anonymity: An enhanced k-anonymity model for privacy preserving data publishing. In Proc. of the 12th ACM SIGKDD, Philadelphia, PA, 2006.
41. X. Xiao and Y. Tao. Anatomy: Simple and effective privacy preservation. In Proc. of the 32nd Very Large Data Bases (VLDB), Seoul, Korea, September 2006.
42. X. Xiao and Y. Tao. Personalized privacy preservation. In Proc. of ACM SIGMOD, Chicago, IL, 2006.
43. X. Xiao and Y. Tao. m-invariance: Towards privacy preserving re-publication of dynamic datasets. In Proc. of ACM SIGMOD, Beijing, China, June 2007.
44. Z. Yang, S. Zhong, and R. N. Wright. Anonymity-preserving data collection. In Proc. of the 11th ACM SIGKDD, pages 334-343, 2005.
45. Z. Yang, S. Zhong, and R. N. Wright. Privacy-preserving classification of customer data without loss of accuracy. In Proc. of the 5th SDM, pages 92-102, 2005.
46. A. C. Yao. Protocols for secure computations. In Proc. of the 23rd IEEE Symposium on Foundations of Computer Science, 1982.