Table of Contents Author Guidelines Submit a Manuscript
Journal of Healthcare Engineering
Volume 2018, Article ID 4073103, 11 pages
https://doi.org/10.1155/2018/4073103
Research Article

Privacy Preserving k-Nearest Neighbor for Medical Diagnosis in e-Health Cloud

Graduate School of Information Security, Korea University, Seoul, Republic of Korea

Correspondence should be addressed to Dong Hoon Lee; rk.ca.aerok@eelhgnod

Received 20 April 2018; Accepted 28 August 2018; Published 15 October 2018

Academic Editor: Ana Margarida Ferreira

Copyright © 2018 Jeongsu Park and Dong Hoon Lee. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J. Vilaplana, F. Solsona, F. Abella, R. Filgueira, and J. Rius, “The cloud paradigm applied to e-Health,” BMC Medical Informatics and Decision Making, vol. 13, no. 1, p. 35, 2013. View at Publisher · View at Google Scholar · View at Scopus
  2. A. Abbas and S. U. Khan, “A review on the state-of-the-art privacy-preserving approaches in the e-health clouds,” IEEE Journal of Biomedical and Health Informatics, vol. 18, no. 4, pp. 1431–1441, 2014. View at Publisher · View at Google Scholar · View at Scopus
  3. 104th United States Congress, Health Insurance Portability and Accountability Act (HIPAA), 1996, http://aspe.hhs.gov/admnsimp/pl104191.htm.
  4. U.S. Department of Health and Human Services, Health Information Technology for Economic and Clinical Health (HITECH) Act, U.S. Department of Health and Human Services, Washington, D.C., USA, 2009, http://www.hhs.gov/hipaa/for-professionals/special-topics/HITECH-act-enforcement-interim-final-rule/index.html.
  5. P. A. Koton, “Using experience in learning and problem solving,” Massachusetts Institute of Technology, Cambridge, MA, USA, 1988, Ph.D. Dissertations. View at Google Scholar
  6. S. Begum, M. U. Ahmed, P. Funk, N. Xiong, and M. Folke, “Case-based reasoning systems in the health sciences: a survey of recent trends and developments,” IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol. 41, no. 4, pp. 421–434, 2011. View at Publisher · View at Google Scholar · View at Scopus
  7. H. Ahn and K.-J. Kim, “Global optimization of case-based reasoning for breast cytology diagnosis,” Expert Systems with Applications, vol. 36, no. 1, pp. 724–734, 2009. View at Publisher · View at Google Scholar · View at Scopus
  8. P. Perner, “An architecture for a CBR image segmentation system,” Engineering Applications of Artificial Intelligence, vol. 12, no. 6, pp. 749–759, 1999. View at Publisher · View at Google Scholar · View at Scopus
  9. J. F. De Paz, S. Rodríguez, J. Bajo, and J. M. Corchado, “Case-based reasoning as a decision support system for cancer diagnosis: a case study,” International Journal of Hybrid Intelligent Systems, vol. 6, no. 2, pp. 97–110, 2009. View at Publisher · View at Google Scholar
  10. S. Montani, L. Portinale, G. Leonardi, R. Bellazzi, and R. Bellazzi, “Case-based retrieval to support the treatment of end stage renal failure patients,” Artificial Intelligence in Medicine, vol. 37, no. 1, pp. 31–42, 2006. View at Publisher · View at Google Scholar · View at Scopus
  11. N. Arshadi and I. Jurisica, “Data mining for case-based reasoning in high-dimensional biological domains,” IEEE Transactions on Knowledge and Data Engineering, vol. 17, no. 8, pp. 1127–1137, 2005. View at Publisher · View at Google Scholar · View at Scopus
  12. C. H. Wan, L. H. Lee, R. Rajkumar, and D. Isa, “A hybrid text classification approach with low dependency on parameter by integrating K-nearest neighbor and support vector machine,” Expert Systems with Applications, vol. 39, no. 15, pp. 11880–11888, 2012. View at Publisher · View at Google Scholar · View at Scopus
  13. B. Yao, F. Li, and X. Xiao, “Secure nearest neighbor revisited,” in Proceedings of IEEE 29th International Conference on Data Engineering (ICDE), pp. 733–744, IEEE, Brisbane Australia, April 2013.
  14. Y. Elmehdwi, B. K. Samanthula, and W. Jiang, “Secure k-nearest neighbor query over encrypted data in outsourced environments,” in Proceedings of IEEE 30th International Conference on Data Engineering (ICDE), pp. 664–675, IEEE, Chicago, IL, USA, March 2014.
  15. B. K. Samanthula, Y. Elmehdwi, and W. Jiang, “k-nearest neighbor classification over semantically secure encrypted relational data,” IEEE Transactions on Knowledge and Data Engineering, vol. 27, no. 5, pp. 1261–1273, 2015. View at Publisher · View at Google Scholar · View at Scopus
  16. Y. Zhu, R. Xu, and T. Takagi, “Secure k-NN computation on encrypted cloud data without sharing key with query users,” in Proceedings of International Workshop on Security in Cloud Computing, pp. 55–60, ACM, Hangzhou, China, May 2013.
  17. E. M. Songhori, S. U. Hussain, A.-R. Sadeghi, and F. Koushanfar, “Compacting privacy-preserving k-nearest neighbor search using logic synthesis,” in Proceedings of 52nd ACM/EDAC/IEEE Design Automation Conference (DAC), pp. 1–6, IEEE, San Francisco, CA, USA, June 2015.
  18. Y. Zhu, Z. Huang, and T. Takagi, “Secure and controllable k-NN query over encrypted cloud data with key confidentiality,” Journal of Parallel and Distributed Computing, vol. 89, pp. 1–12, 2016. View at Publisher · View at Google Scholar · View at Scopus
  19. R. Xu, K. Morozov, Y. Yang, J. Zhou, and T. Takagi, “Privacy-preserving k-nearest neighbour query on outsourced database,” in Proceedings of Australasian Conference on Information Security and Privacy, pp. 181–197, Springer, Melbourne, Australia, July 2016.
  20. F. Li, R. Shin, and V. Paxson, “Exploring privacy preservation in outsourced k-nearest neighbors with multiple data owners,” in Proceedings of 2015 ACM Workshop on Cloud Computing Security Workshop, pp. 53–64, ACM, Denver, CO, USA, October 2015.
  21. H. Rong, H. Wang, J. Liu, and M. Xian, “Privacy-preserving k-nearest neighbor computation in multiple cloud environments,” IEEE Access, vol. 4, pp. 9589–9603, 2016. View at Publisher · View at Google Scholar · View at Scopus
  22. M. Burkhart and X. Dimitropoulos, “Privacy-preserving distributed network troubleshooting—bridging the gap between theory and practice,” ACM Transactions on Information and System Security (TISSEC), vol. 14, no. 4, p. 31, 2011. View at Publisher · View at Google Scholar · View at Scopus
  23. M. Van Dijk and A. Juels, “On the impossibility of cryptography alone for privacy-preserving cloud computing,” HotSec, vol. 10, pp. 1–8, 2010. View at Google Scholar
  24. O. Goldreich, S. Micali, and A. Wigderson, “How to play any mental game,” in Proceedings of Nineteenth Annual ACM Symposium on Theory of Computing, pp. 218–229, ACM, New York, NY, USA, May 1987.
  25. M. Burkhart, M. Strasser, D. Many, and X. Dimitropoulos, “SEPIA: Privacy-preserving aggregation of multi-domain network events and statistics,” Network, vol. 1, Article ID 101101, 2010. View at Google Scholar
  26. R. Cramer, I. Damgard, and J. Buus Nielsen, Secure Multiparty Computation and Secret Sharing-An Information Theoretic Approach Book Draft, Cambridge University Press, Cambridge, UK, 2012.
  27. D. Beaver, “Efficient multiparty protocols using circuit randomization,” in Proceedings of Annual International Cryptology Conference, pp. 420–432, Springer, Santa Barbara, California, USA, August 1991.
  28. M. Burkhart, M. Strasser, D. Many, and X. Dimitropoulos, SEPIA MPC Library, http://sepia.ee.ethz.ch/download.html.
  29. I. Damgård, M. Fitzi, E. Kiltz, J. Buus Nielsen, and T. Toft, “Unconditionally secure constant-rounds multi-party computation for equality, comparison, bits and exponentiation,” in Proceedings of Theory of Cryptography Conference, pp. 285–304, Springer, New York, NY, USA, March 2006.
  30. T. Nishide and K. Ohta, “Multiparty computation for interval, equality, and comparison without bit-decomposition protocol,” in Proceedings of International Workshop on Public Key Cryptography, pp. 343–360, Springer, Beijing, China, April 2007.
  31. T. Cover and P. Hart, “Nearest neighbor pattern classification,” IEEE Transactions on Information Theory, vol. 13, no. 1, pp. 21–27, 1967. View at Publisher · View at Google Scholar · View at Scopus
  32. V. S. Verykios, E. Bertino, I. N. Fovino et al., “State-of-the-art in privacy preserving data mining,” ACM Sigmod Record, vol. 33, no. 1, pp. 50–57, 2004. View at Publisher · View at Google Scholar · View at Scopus
  33. M. Shaneck, Y. Kim, and V. Kumar, “Privacy preserving nearest neighbor search,” Machine Learning in Cyber Trust, Springer, Boston, MA, 2009. View at Google Scholar
  34. T. Veugen, “Linear round bit-decomposition of secret-shared values,” IEEE Transactions on Information Forensics and Security, vol. 10, no. 3, pp. 498–506, 2015. View at Publisher · View at Google Scholar · View at Scopus
  35. Y. Lindell and B. Pinkas, “Privacy preserving data mining,” in Proceedings of Annual International Cryptology Conference, pp. 36–54, Springer, Santa Barbara, California, USA, August 2000.
  36. Y. Qi and M. J. Atallah, “Efficient privacy-preserving k-nearest neighbor search,” in Proceedings of 28th International Conference on Distributed Computing Systems, 2008, pp. 311–319, IEEE, Santa Barbara, California, USA, August 2008.
  37. L. Xiong, S. Chitti, and L. Liu, “Mining multiple private databases using a kNN classifier,” in Proceedings of 2007 ACM symposium on Applied computing, pp. 435–440, ACM, Seoul, Korea, March 2007.
  38. J. Vaidya and C. Clifton, “Privacy-preserving top-k queries,” in Proceedings of 21st International Conference on Data Engineering, 2005, pp. 545-546, IEEE, Tokyo, Japan, April 2005.
  39. J. Vaidya and C. W. Clifton, “Privacy-preserving kth element score over vertically partitioned data,” IEEE Transactions on Knowledge and Data Engineering, vol. 21, no. 2, pp. 253–258, 2009. View at Publisher · View at Google Scholar · View at Scopus
  40. R. Fagin, “Combining fuzzy information from multiple systems,” in Proceedings of the fifteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems, pp. 216–226, ACM, Montreal, Canada, June 1996.
  41. G. Aggarwal, N. Mishra, and B. Pinkas, “Secure computation of the k th-ranked element,” in Proceedings of International Conference on the Theory and Applications of Cryptographic Techniques, pp. 40–55, Springer, Interlaken, Switzerland, May 2004.
  42. K. V. Jónsson, G. Kreitz, and M. Uddin, “Secure multi-party sorting and applications,” IACR Cryptology ePrint Archive, vol. 2011, p. 122, 2011. View at Google Scholar