Privacy Preserving in Horizontally Partitioned Data Based on association Rules Mining

Dharmik Mkawana; Krunal Panchal

Privacy Preserving in Horizontally Partitioned Data Based on association Rules Mining

May 2016

Vol-2, Issue-3

Paper ID: 2331

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Information Technology

Keywords

Data Mining Elliptic Curve Cryptography EMHS Privacy Privacy Preserving Association Rule Mining

Abstract

The advances of data mining techniques played an important role in many areas for various applications. In context of privacy and security issues, the problems caused by association rule mining technique are recently investigated. The misuse of this technique may disclose the database owner’s sensitive information to others. Hence, the privacy of individuals is not maintained. Many of the researchers have recently made an effort to preserve privacy of sensitive knowledge or information in a real database. In this paper, we have modified EMHS Algorithm to improve its efficiency by using Elliptic Curve Cryptography. Analysis of the experiment on various datasets show that proposed algorithm is efficient compared to EMHS in terms of computation time.

License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author Information

#	Name	Institute / Affiliation
1	Dharmik Mkawana	L. J. INSTITUTE OF ENGINERRING AND TECHNOLOGY
2	Krunal Panchal	L. J. INSTITUTE OF ENGINERRING AND TECHNOLOGY

How to Cite

Use the following formats to cite this article in your research.

APA Style

Mkawana, Dharmik & Panchal, Krunal (2016). Privacy Preserving in Horizontally Partitioned Data Based on association Rules Mining. International Journal of Advance Research and Innovative Ideas In Education, 2(3), 1063-1069.

MLA Style

Mkawana, Dharmik, and Krunal Panchal. "Privacy Preserving in Horizontally Partitioned Data Based on association Rules Mining." International Journal of Advance Research and Innovative Ideas In Education, vol. 2, no. 3, 2016, pp. 1063-1069.

IEEE Style

Dharmik Mkawana and Krunal Panchal, "Privacy Preserving in Horizontally Partitioned Data Based on association Rules Mining," International Journal of Advance Research and Innovative Ideas In Education, vol. 2, no. 3, pp. 1063-1069, 2016.

Vancouver Style

Mkawana Dharmik, Panchal Krunal. Privacy Preserving in Horizontally Partitioned Data Based on association Rules Mining. International Journal of Advance Research and Innovative Ideas In Education. 2016;2(3):1063-1069.

Harvard Style

Mkawana, Dharmik & Panchal, Krunal (2016) 'Privacy Preserving in Horizontally Partitioned Data Based on association Rules Mining', International Journal of Advance Research and Innovative Ideas In Education, 2(3), pp. 1063-1069.

Chicago Style

Mkawana, Dharmik and Krunal Panchal. "Privacy Preserving in Horizontally Partitioned Data Based on association Rules Mining." International Journal of Advance Research and Innovative Ideas In Education 2, no. 3 (2016): 1063-1069.

Turabian Style

Mkawana, Dharmik and Krunal Panchal. "Privacy Preserving in Horizontally Partitioned Data Based on association Rules Mining." International Journal of Advance Research and Innovative Ideas In Education 2, no. 3 (2016): 1063-1069.