Table of Contents Author Guidelines Submit a Manuscript
Wireless Communications and Mobile Computing
Volume 2018, Article ID 2385150, 10 pages
https://doi.org/10.1155/2018/2385150
Research Article

Securely Outsourcing ID3 Decision Tree in Cloud Computing

1Harbin Institute of Technology, Shenzhen, Shenzhen 518055, China
2Jinan University, Guangzhou, China
3Henan Normal University, Henan, China
4School of Computer Science, Guangzhou University, China

Correspondence should be addressed to Zoe L. Jiang; nc.ude.tih@gnaijleoz

Received 2 May 2018; Accepted 2 September 2018; Published 4 October 2018

Academic Editor: Jaime Lloret

Copyright © 2018 Ye Li et al. 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. Y. Lindell and B. Pinkas, “Privacy preserving data mining,” Journal of Cryptology, vol. 15, no. 3, pp. 177–206, 2002. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  2. R. Agrawal and R. Srikant, “Privacy-preserving data mining,” ACM SIGMOD Record, vol. 29, no. 2, pp. 439–450, 2000. View at Publisher · View at Google Scholar
  3. D. Liu, E. Bertino, and X. Yi, “Privacy of outsourced k-means clustering,” in Proceedings of the 9th ACM Symposium on Information, Computer and Communications Security, ASIA CCS 2014, pp. 123–133, June 2014. View at Publisher · View at Google Scholar · View at Scopus
  4. P. Li, J. Li, Z. Huang, C.-Z. Gao, W.-B. Chen, and K. Chen, “Privacy-preserving outsourced classification in cloud computing,” Cluster Computing, pp. 1–10, 2017. View at Publisher · View at Google Scholar · View at Scopus
  5. F. Emekci, O. D. Sahin, D. Agrawal, and A. El Abbadi, “Privacy preserving decision tree learning over multiple parties,” Data & Knowledge Engineering, vol. 63, no. 2, pp. 348–361, 2007. View at Publisher · View at Google Scholar · View at Scopus
  6. P. Lory, “Enhancing the Efficiency in Privacy Preserving Learning of Decision Trees in Partitioned Databases,” in Privacy in Statistical Databases, vol. 7556 of Lecture Notes in Computer Science, pp. 322–335, Springer Berlin Heidelberg, Berlin, Heidelberg, 2012. View at Publisher · View at Google Scholar
  7. J. Vaidya and C. Clifton, “Privacy-preserving K-means clustering over vertically partitioned data,” in Proceedings of the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '03), pp. 206–215, Washington, DC , USA, August 2003. View at Publisher · View at Google Scholar · View at Scopus
  8. J. Zhan, S. Matwin, and L. W. Chang, “Privacy-Preserving Naive Bayesian Classification over Horizontally Partitioned Data,” in Data Mining: Foundations and Practice, vol. 118 of Studies in Computational Intelligence, pp. 529–538, Springer Berlin Heidelberg, Berlin, Heidelberg, 2008. View at Publisher · View at Google Scholar
  9. S. Han and W. K. Ng, “Multi-party privacy-preserving decision trees for arbitrarily partitioned data,” International Journal of Intelligent Control and Systems, vol. 12, no. 4, 2007. View at Google Scholar
  10. T. Li, J. Li, Z. Liu, P. Li, and C. Jia, “Differentially private Naive Bayes learning over multiple data sources,” Information Sciences, vol. 444, pp. 89–104, 2018. View at Publisher · View at Google Scholar · View at MathSciNet
  11. C. Gao, Q. Cheng, P. He, W. Susilo, and J. Li, “Privacy-preserving Naive Bayes classifiers secure against the substitution-then-comparison attack,” Information Sciences, vol. 444, pp. 72–88, 2018. View at Publisher · View at Google Scholar · View at MathSciNet
  12. J. Shen, T. Zhou, X. Chen, J. Li, and W. Susilo, “Anonymous and Traceable Group Data Sharing in Cloud Computing,” IEEE Transactions on Information Forensics and Security, vol. 13, no. 4, pp. 912–925, 2018. View at Publisher · View at Google Scholar
  13. Z. Cai, H. Yan, P. Li, Z.-A. Huang, and C. Gao, “Towards secure and flexible EHR sharing in mobile health cloud under static assumptions,” Cluster Computing, vol. 20, no. 3, pp. 2415–2422, 2017. View at Publisher · View at Google Scholar · View at Scopus
  14. J. Li, Y. K. Li, X. Chen, P. P. C. Lee, and W. Lou, “A Hybrid Cloud Approach for Secure Authorized Deduplication,” IEEE Transactions on Parallel and Distributed Systems, vol. 26, no. 5, pp. 1206–1216, 2015. View at Publisher · View at Google Scholar · View at Scopus
  15. Z. Liu, Y. Huang, J. Li, X. Cheng, and C. Shen, “DivORAM: Towards a practical oblivious RAM with variable block size,” Information Sciences, vol. 447, pp. 1–11, 2018. View at Publisher · View at Google Scholar · View at MathSciNet
  16. X. Chen, J. Li, J. Weng, J. Ma, and W. Lou, “Verifiable computation over large database with incremental updates,” Institute of Electrical and Electronics Engineers. Transactions on Computers, vol. 65, no. 10, pp. 3184–3195, 2016. View at Google Scholar · View at MathSciNet
  17. J. Shen, C. Wang, T. Li, X. Chen, X. Huang, and Z.-H. Zhan, “Secure data uploading scheme for a smart home system,” Information Sciences, vol. 453, pp. 186–197, 2018. View at Publisher · View at Google Scholar · View at MathSciNet
  18. S. Chen, G. Wang, G. Yan, and D. Xie, “Multi-dimensional fuzzy trust evaluation for mobile social networks based on dynamic community structures,” Concurrency and Computation: Practice and Experience, vol. 29, no. 7, p. e3901, 2017. View at Publisher · View at Google Scholar
  19. E. Luo, Q. Liu, J. H. Abawajy, and G. Wang, “Privacy-preserving multi-hop profile-matching protocol for proximity mobile social networks,” Future Generation Computer Systems, vol. 68, pp. 222–233, 2017. View at Publisher · View at Google Scholar · View at Scopus
  20. X. F. Chen, J. Li, J. Ma, Q. Tang, and W. Lou, “New algorithms for secure outsourcing of modular exponentiations,” IEEE Transactions on Parallel and Distributed Systems, vol. 25, no. 9, pp. 2386–2396, 2014. View at Publisher · View at Google Scholar
  21. R. Bost, R. A. Popa, S. Tu, and S. Goldwasser, “Machine Learning Classification over Encrypted Data,” in Proceedings of the Network and Distributed System Security Symposium, San Diego, CA. View at Publisher · View at Google Scholar
  22. A. Peter, E. Tews, and S. Katzenbeisser, “Efficiently outsourcing multiparty computation under multiple keys,” IEEE Transactions on Information Forensics and Security, vol. 8, no. 12, pp. 2046–2058, 2013. View at Publisher · View at Google Scholar · View at Scopus
  23. G. Jagannathan, K. Pillaipakkamnatt, and R. N. Wright, “A Practical Differentially Private Random Decision Tree Classifier,” in Proceedings of the 2009 IEEE International Conference on Data Mining Workshops (ICDMW), pp. 114–121, Miami, FL, USA, December 2009. View at Publisher · View at Google Scholar
  24. B. Gilburd, A. Schuster, and R. Wolff, “Privacy-preserving data mining on data grids in the presence of malicious participants,” in Proceedings of the Proceedings. 13th IEEE International Symposium on High performance Distributed Computing, 2004., pp. 225–234, Honolulu, HI, USA. View at Publisher · View at Google Scholar
  25. D. Shah and S. Zhong, “Two methods for privacy preserving data mining with malicious participants,” Information Sciences, vol. 177, no. 23, pp. 5468–5483, 2007. View at Publisher · View at Google Scholar · View at Scopus
  26. P. Li, J. Li, Z. Huang et al., “Multi-key privacy-preserving deep learning in cloud computing,” Future Generation Computer Systems, vol. 74, pp. 76–85, 2017. View at Publisher · View at Google Scholar
  27. Q. Lin, H. Yan, Z. Huang, W. Chen, J. Shen, and Y. Tang, “An ID-based linearly homomorphic signature scheme and its application in blockchain,” IEEE Access, vol. PP, no. 99, pp. 1–1, 2018. View at Publisher · View at Google Scholar
  28. J. Xu, L. Wei, Y. Zhang, A. Wang, F. Zhou, and C. Gao, “Dynamic Fully Homomorphic encryption-based Merkle Tree for lightweight streaming authenticated data structures,” Journal of Network and Computer Applications, vol. 107, pp. 113–124, 2018. View at Publisher · View at Google Scholar
  29. J. Shen, Z. Gui, S. Ji, J. Shen, H. Tan, and Y. Tang, “Cloud-aided lightweight certificateless authentication protocol with anonymity for wireless body area networks,” Journal of Network and Computer Applications, vol. 106, pp. 117–123, 2018. View at Publisher · View at Google Scholar
  30. X. Zhang, Y. Tan, C. Liang, Y. Li, and J. Li, “A Covert Channel Over VoLTE via Adjusting Silence Periods,” IEEE Access, vol. 6, pp. 9292–9302, 2018. View at Publisher · View at Google Scholar
  31. Y. Wang, T. Li, H. Qin et al., “A brief survey on secure multi-party computing in the presence of rational parties,” Journal of Ambient Intelligence and Humanized Computing, vol. 6, no. 6, pp. 807–824, 2015. View at Publisher · View at Google Scholar · View at Scopus
  32. P. Paillier, “Public-key cryptosystems based on composite degree residuosity classes,” in Advances in Cryptology—EUROCRYPT ’99, vol. 1592, pp. 223–238, Springer, 1999. View at Publisher · View at Google Scholar · View at MathSciNet
  33. L. Li, R. Lu, K.-K. R. Choo, A. Datta, and J. Shao, “Privacy-Preserving-Outsourced Association Rule Mining on Vertically Partitioned Databases,” IEEE Transactions on Information Forensics and Security, vol. 11, no. 8, pp. 1547–1861, 2016. View at Publisher · View at Google Scholar · View at Scopus
  34. P. Mohassel, M. Rosulek, and Y. Zhang, “Fast and Secure Three-party Computation,” in Proceedings of the the 22nd ACM SIGSAC Conference, pp. 591–602, Denver, Colorado, USA, October 2015. View at Publisher · View at Google Scholar
  35. M. Naor, “Bit commitment using pseudorandomness,” Journal of Cryptology, vol. 4, no. 2, pp. 151–158, 1991. View at Google Scholar · View at Scopus
  36. H. Cheng, Z. Su, N. Xiong, and Y. Xiao, “Energy-efficient node scheduling algorithms for wireless sensor networks using Markov Random Field model,” Information Sciences, vol. 329, pp. 461–477, 2016. View at Publisher · View at Google Scholar · View at Scopus
  37. H. Cheng, N. Xiong, A. V. Vasilakos, L. Tianruo Yang, G. Chen, and X. Zhuang, “Nodes organization for channel assignment with topology preservation in multi-radio wireless mesh networks,” Ad Hoc Networks, vol. 10, no. 5, pp. 760–773, 2012. View at Publisher · View at Google Scholar · View at Scopus