Privacy-preserving k-NN for small and large data sets

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2007, Pages 699-704

  Amirbekyan, Artak ^a   Estivill Castro, Vladimir ^a  

^a GRIFFITH UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ADMINISTRATIVE DATA PROCESSING; DATA MINING; DECISION SUPPORT SYSTEMS; INFORMATION MANAGEMENT; MINING; SEARCH ENGINES; SOLUTIONS;

DETECTION TASKS; EFFICIENT SOLUTIONS; INTERNATIONAL CONFERENCES; LARGE DATA SETS; MINKOWSKI METRICS; PRACTICAL SOLUTIONS; PRIVACY-PRESERVING; SMALL DATA SETS;

CANNING;

EID: 49549105074     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDMW.2007.67     Document Type: Conference Paper

References (27)

1. A. Amirbekyan and V. Estivill-Castro. Privacy preserving DBSCAN for vertically partitioned data. In IEEE ISI, p. 141-153, San Diego, CA, USA, 2006.
2. A. Amirbekyan and V. Estivill-Castro. The privacy of κ-nn retrieval for horizontal partitioned data - new methods and applications. (ADC2007), v. 63, p. 33-42, Ballarat, Victoria, Australia, 2007.
3. S. Arya, D. M. Mount, N. S. Netanyahu, R. Silverman, and A. Y. Wu. An optimal algorithm for approximate nearest neighbor searching. In 5th ACM-SIAM Symposium on Discrete Algorithms, p. 573-582, 1994.
4. S. Avidan and M. Butman. Blind vision. Computer Vision - ECCV 2006, Part III, volume 3953 of LNCS, p. 1-13, Graz, Austria, 2006.
5. K. Beyer, J. Goldstein, R. Ramakrishnan, and U. Shaft. When is nearest neighbor meaningful ? In ICDT, p. 217-225, Jerusalem, Israel, 1999.
6. C. Cachin. Efficient private bidding and auctions with an oblivious third party. In Proc. of the 6th ACM Conference on Computer and Communications Security, p. 120-127, Singapore, 1999.
7. P. Ciaccia and M. Patella. PAC nearest neighbor queries: Approximate and controlled search in high-dimensional and metric spaces. In Proc. of the ICDE, p. 244-255, San Jose, CA, 2000.
8. W. Du and M.J. Atallah. Privacy-preserving cooperative statistical analysis. In Proc.of the (ACSAC), p. 102-110, New Orleans, Louisiana, 2001.
9. W. Du and Z. Zhan. Building decision tree classifier on private data. Privacy, Security and Data Mining, p. 1-8, Sydney, Australia, 2002. IEEE ICDM Workshop Proceedings.
10. R Fagin. Combining fuzzy information from multiple systems. In Proceedings of the ACM Symposium on Principles of Database Systems, p. 216-226, Montreal, Canada, 1996.
11. H. Ferhatosmanoglu, E. Tuncel, D. Agrawal, and A. El Abbadi. Approximate nearest neighbor searching in multimedia databases. In 7th IEEE (ICDE), p. 503-511, Germany, 2002.
12. O. Goldreich. The Foundations of Cryptography, volume 2, chapter General Cryptographic Protocols. Cambridge University Press, 2004.
13. O. Goldreich, S. Micali, and A. Wigderson. How to play any mental game (extended abstract). Proc. of the 19th ACM Annual Symposium on Theory of Computing, p. 218-229, New York, 1987.
14. M.E. Houle. Navigating massive data sets via local clustering. 9th ACM SIGKDD, p. 547-552, Washington, DC, 2003.
15. M.E. Houle. SASH: a spatial approximation sample hierarchy for similarity. Technical Report RT-0517, IBM Tokyo Research Laboratory, 2003.
16. M.E. Houle and J. Sakuma. Fast approximate similarity search in extremely high-dimensional data sets. In ICDE, p. 619-630, Tokyo, Japan, 2005.
17. I. Ioannidis and A. Grama. An efficient protocol for Yao's millionaires' problem. In 36th HICSS, p. 205, Big Island, HI, 2003.
18. M. Kantarcioǧlu and C. Clifton. Privately computing a distributed κ-nn classifier. PKDD, v. 3202, p. 279-290. LNCS, 2004.
19. J. Mena. Investigative Data Mining for Security and Criminal Detection. Butterworth-Heinemann, US, 2003.
20. N. Roussopoulos, S. Kelly, and F. Vincent. Nearest neighbor queries. In Proceedings of the ACM SIGMOD, p. 71-79, San Jose, CA, 1995.
21. M. Shaneck, Y. Kim, and V. Kumar. Privacy preserving nearest neighbor search. 2006 IEEE ICDM Workshop on Privacy Aspects of Data Mining, 2006.
22. J. Vaidya and C. C. Clifton. Privacy-preserving κ-means clustering over vertically partitioned data. In Proceedings of the SIGKDD-ACM, p. 206-215, Washington, DC, 2003.
23. J. Vaidya and C. Clifton. Privacy-preserving outlier detection. In 4th IEEE (ICDM), Brighton, UK, 2004.
24. J. Vaidya and C. Clifton. Privacy-preserving top-κ queries. In ICDE , p. 545-546, Tokyo, 2005.
25. J. Vaidya, C. Clifton, and M. Zhu. Privacy Preserving Data Mining, volume 19 of Advances in Information Security. Springer, New York, 2006.
26. P. van der Putten and M. van Someren. CoIL challenge 2000: The insurance company case. Technical Report 2000-09, Leiden Institute of Advanced Computer Science, Amsterdam, 2000.
27. A.C. Yao. Protocols for secure computation. In IEEE Symposium of Foundations of Computer Science, p. 160-164. 1982.