Privacy-Preserving Machine Learning Algorithms for Big Data Systems

Proceedings - International Conference on Distributed Computing Systems

Volumn 2015-July, Issue , 2015, Pages 318-327

  Xu, Kaihe ^a   Yue, Hao ^a   Guo, Linke ^b   Guo, Yuanxiong ^c   Fang, Yuguang ^a  

^a J Crayton Pruitt Family Department of Biomedical Engineering   (United States)

^b State University of New York   (United States)

^c Oklahoma State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIG DATA; COMPUTER SOFTWARE; CRYPTOGRAPHY; DATA PRIVACY; LEARNING ALGORITHMS; MACHINE LEARNING;

CRYPTOGRAPHIC OPERATIONS; DISTRIBUTED DATA PROCESSING; EXTENSIVE SIMULATIONS; HEALTH-CARE SYSTEM; HIDDEN INFORMATION; MULTIPLE ORGANIZATIONS; PRIVACY PRESERVATION; PRIVACY PRESERVING;

DATA SHARING;

EID: 84944328461     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDCS.2015.40     Document Type: Conference Paper

References (31)

1. R. Agrawal and R. Srikant. Privacy-preserving data mining. In Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data, SIGMOD '00, pages 439-450, New York, NY, USA, 2000. ACM
2. K. Bache and M. Lichman. UCI machine learning repository, 2013
3. P. Baldi, P. Sadowski, and D. Whiteson. Searching for exotic particles in high-energy physics with deep learning. Nat Commun, 5, July 2014
4. S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein. Distributed optimization and statistical learning via the alternating direction method of multipliers. Found. Trends Mach. Learn., 3(1):1-122, Jan. 2011
5. C. J. C. Burges. A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery, 2:121-167, 1998
6. C.-C. Chang and C.-J. Lin. LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2:27:1-27:27, 2011
7. K. Chaudhuri and C. Monteleoni. Privacy-preserving logistic regression. In NIPS, pages 289-296, 2008
8. K. Chen and L. Liu. Privacy preserving data classification with rotation perturbation. In ICDM, pages 589-592, 2005
9. C. Clifton, M. Kantarcioglu, J. Vaidya, X. Lin, and M. Y. Zhu. Tools for privacy preserving distributed data mining. SIGKDD Explor. Newsl., 4(2):28-34, Dec. 2002
10. C. Cortes and V. Vapnik. Support-vector networks. Mach. Learn., 20(3):273-297, Sept. 1995
11. Y. Duan, J. Canny, and J. Zhan. P4p: Practical large-scale privacypreserving distributed computation robust against malicious users. In Proceedings of the 19th USENIX Conference on Security, USENIX Security'10, pages 14-14, Berkeley, CA, USA, 2010. USENIX Association
12. J. Ekanayake, H. Li, B. Zhang, T. Gunarathne, S.-H. Bae, J. Qiu, and G. Fox. Twister: A runtime for iterative mapreduce. In Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing, HPDC '10, pages 810-818, New York, NY, USA, 2010. ACM
13. P. K. Fong and J. Weber-Jahnke. Privacy preserving decision tree learning using unrealized data sets. Knowledge and Data Engineering, IEEE Transactions on, 24(2):353-364, Feb 2012
14. P. K. Fong and J. Weber-Jahnke. Privacy preserving decision tree learning using unrealized data sets. Knowledge and Data Engineering, IEEE Transactions on, 24(2):353-364, Feb 2012
15. P. A. Forero, A. Cano, and G. B. Giannakis. Consensus-based distributed support vector machines. J. Mach. Learn. Res., 99:1663-1707, August 2010
16. G. H. Golub and C. F. Van Loan. Matrix Computations (3rd Ed.). Johns Hopkins University Press, Baltimore, MD, USA, 1996
17. M. Kantarcioglu and C. Clifton. Privacy-preserving distributed mining of association rules on horizontally partitioned data. IEEE Trans. on Knowl. and Data Eng., 16(9):1026-1037, Sept. 2004
18. M. Kantarcioglu and C. Clifton. Privacy-preserving distributed mining of association rules on horizontally partitioned data. IEEE Trans. Knowl. Data Eng., 16(9):1026-1037, 2004
19. S. Laur, H. Lipmaa, and T. Mielikainen. Cryptographically private support vector machines. In Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '06, pages 618-624, New York, NY, USA, 2006. ACM
20. Y. Lindell and B. Pinkas. Privacy preserving data mining. J. Cryptology, 15(3):177-206, 2002
21. O. L. Mangasarian and E. W. Wild. Privacy-preserving classification of horizontally partitioned data via random kernels. In DMIN'08, pages 473-479, 2008
22. O. L. Mangasarian, E. W. Wild, and G. M. Fung. Privacy-preserving classification of vertically partitioned data via random kernels. ACM Trans. Knowl. Discov. Data, 2(3):12:1-12:16, Oct. 2008
23. E. Osuna, R. Freund, and F. Girosi. An improved training algorithm for support vector machines. In Neural Networks for Signal Processing [1997] VII. Proceedings of the 1997 IEEE Workshop pages 276-285, Sep 1997.
24. J. Platt. Sequential minimal optimization: A fast algorithm for training support vector machines. Technical Report MSR-TR-98-14, Microsoft Research, April 1998
25. B. Scholkopf and A. J. Smola. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. MIT Press, Cambridge, MA, USA, 2001
26. J. Vaidya and C. Clifton. Privacy preserving association rule mining in vertically partitioned data. In Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '02, pages 639-644, New York, NY, USA, 2002. ACM
27. J. Vaidya and C. Clifton. Privacy preserving association rule mining in vertically partitioned data. In KDD, pages 639-644, 2002
28. H. Yu, X. Jiang, and J. Vaidya. Privacy-preserving svm using nonlinear kernels on horizontally partitioned data. In Proceedings of the 2006 ACM symposium on Applied computing, SAC '06, pages 603-610, New York, NY, USA, 2006. ACM
29. H. Yu, X. Jiang, and J. Vaidya. Privacy-preserving svm using nonlinear kernels on horizontally partitioned data. In Proceedings of the 2006 ACM Symposium on Applied Computing, SAC '06, pages 603-610, New York, NY, USA, 2006. ACM
30. J. Yuan and S. Yu. Privacy preserving back-propagation neural network learning made practical with cloud computing. Parallel and Distributed Systems, IEEE Transactions on, 25(1):212-221, Jan 2014
31. J. Z. Zhan and S. Matwin. Privacy-preserving support vector machine classification. IJIIDS, 1(3/4):356-385, 2007