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Hash-Based Rule Mining Algorithm in Data-Intensive Homogeneous Cloud Environment

  • Raghvendra Kumar
  • Prasant Kumar Pattnaik
  • Yogesh Sharma
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 379)

Abstract

Today Innovative Technology is used to analyze and manipulate huge amount of data in the cloud computing environment. It is very challenging task because the privacy and security are the main issue. Because the scenario of the cloud environment is given, then the distributed database comes in the picture as well as privacy. In this paper, we used the concept of pseudo random number, and for finding the strong Association rule in the database, we used the Inverted hashing and pruning as well as distributing the database into the different number of cloud nodes, and finding the global result, we used Distributed secure sum protocol in the homogenous cloud environments, where the number of attributes will be same, the number of transactions wearies from node to node.

References

  1. 1.
    Yao, A.C.: Protocol for secure computations. In: Proceedings of the 23rd annual IEEE symposium on foundation of computer science, pp. 160–164. IEEE Press, Chicago, USA, 1982Google Scholar
  2. 2.
    Yao, A.C.C.: How to generate and exchange secrets (extended abstract). In: Proceedings of the 27th IEEE Symposium on Foundations of Computer Science (FOCS). IEEE Press USA (1986)Google Scholar
  3. 3.
    Agrawal, R. et al.: Mining association rules between sets of items in large database. In: Proceedings of ACM SIGMOD’93, pp. 207–216. D.C. ACM Press, Washington (1993)Google Scholar
  4. 4.
    Li, D.Y., Li, D.R.: Mining association rule with Linuistic cloud model [J]. J. Softw. 2, 143–158 (2000)Google Scholar
  5. 5.
    Clifton, C., Lin, D.: Tool for privacy preserving distributed data mining [J]. SIGKDD Explorations 2, 28–34 (2002)Google Scholar
  6. 6.
    Lindell, Y.: Privacy preserving data mining [J]. J. Cryptog. 3, 177–206 (2002)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Chen, X., Orlowska, M.: A new framework for privacy preserving data sharing. In: Proceedings of the 4th IEEE ICDM Workshop: Privacy and Security Aspects of Data Mining, pp. 47–56. IEEE Computer Society (2004)Google Scholar
  8. 8.
    Mielikainen, T.: On inverse frequent set mining. In: Proceedings 3rd IEEE ICDM Workshop on Privacy Preserving Data Mining, pp. 18–23. IEEE Computer Society (2003)Google Scholar
  9. 9.
    Du, W., Atallah, M.: Secure Multi-party Computation: A Review and Open Problems. CERIAS Tech. Report 2001-51, Purdue University (2001)Google Scholar
  10. 10.
    Srikant, R., Agrawal, R.: Mining generalized association rules. In: VLDB’95, pp. 479–488 Zurich, Switzerland, 1994Google Scholar
  11. 11.
    Agrawal, R., Srikant, R.: Privacy-preserving data mining. In: Proceedings of the 2000 ACM SIGMOD on management of data, pp. 439–450. ACM Press, Dallas, TX USA (2000)Google Scholar
  12. 12.
    Lindell, Y., Pinkas, B.: Privacy preserving data mining. In: Proceedings of 20th Annual International Cryptology Conference (CRYPTO), Santa Barbara, California, USA (2000)Google Scholar
  13. 13.
    Clifton, C., Kantarcioglou, M., Xiadong, L., Michaed, Y.Z.: Tools for privacy preserving distributed data mining. SIGKDD Explorations 4(2), 43–48 (2002)Google Scholar
  14. 14.
    Vaidya, J., Clifton, C.: Privacy-Preserving Decision Trees over vertically partitioned data. Lecture Notes in Computer Science, vol. 3654 (2005)Google Scholar
  15. 15.
    Ioannidis, I., Grama, A., Atallah, M.: A secure protocol for computing dot-products in clustered and distributed environments. In: Proceedings of International Conference on Parallel Processing, pp. 379–384, 18–21 Aug 2002Google Scholar

Copyright information

© Springer India 2016

Authors and Affiliations

  • Raghvendra Kumar
    • 1
  • Prasant Kumar Pattnaik
    • 2
  • Yogesh Sharma
    • 1
  1. 1.Faculty of Engineering and TechnologyJodhpur National UniversityJodhpurIndia
  2. 2.School of Computer EngineeringKIIT UniversityBhubaneswarIndia

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