An Overview of Secure Mining of Association Rules in Horizontally Distributed Databases

Authors

  • Patil S Asst.Prof, GHRIEM, Jalgaon
  • Patil HS GHRIEM, Jalgaon

Keywords:

Privacy Preserving Data Mining, Distributed Computation, Frequent Item sets, Association Rules

Abstract

In this paper, propose a protocol for secure mining of association rules in horizontally distributed databases. Now a day the current leading protocol is Kantarcioglu and Clifton. This protocol is based on the Fast Distributed Mining (FDM) algorithm which is an unsecured distributed version of the Apriori algorithm. The main ingredients in this protocol are two novel secure multi-party algorithms 1. That computes the union of private subsets that each of the interacting players hold, and 2. Tests the inclusion of an element held by one player in a subset held by another. In this protocol offers enhanced privacy with respect to the other one. Differences in this protocol, it is simpler and is significantly more efficient in terms of communication rounds, communication cost and computational cost [1]

References

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. M. Kantarcioglu and C. Clifton. Privacypreserving distributed mining of association rules on horizontally partitioned data. IEEE Transactions on Knowledge and Data Engineering, 16:1026-1037, 2004.

. T. Tassa and D. Cohen. Anonymization of centralized and distributed social networks by sequential clustering. IEEE Transactions on Knowledge and Data Engineering, 2012.

. T. Tassa and D. Cohen. Anonymization of centralized and distributed social networks by sequential clustering. IEEE Transactions on Knowledge and Data Engineering, 2012.

. J. Vaidya and C. Clifton. Privacy preserving association rule mining in vertically partitioned data. In KDD, pages 639-644, 2002.

. S. Zhong, Z. Yang, and R.N. Wright. Privacyenhancing kanonymization of customer data. In PODS, pages 139-147, 2005.

. David W. Cheungt Jiawei Hans Vincent T. NgttAda W. Fuss Yongjian FuI. "A Fast Distributed Algorithm for Mining Association Rules".

. Shikha Sharma, Prof. Pooja Jain, " A Novel Data Mining Approach for Information Hiding".

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Published

2024-02-26

How to Cite

Patil, S., & Patil, H. S. (2024). An Overview of Secure Mining of Association Rules in Horizontally Distributed Databases. COMPUSOFT: An International Journal of Advanced Computer Technology, 3(01), 491–493. Retrieved from https://ijact.in/index.php/j/article/view/87

Issue

Section

Review Article

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