General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Mia Hu
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
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Prof. Mehmet Sahinoglu
Computer Science Department, Troy University, USA
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.

IJCTE 2022 Vol.14(1): 1-8 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2022.V14.1303

Privacy-Preserving Association Rule Mining Considering Multi-objective through an Evolutionary Algorithm

Darshana H. Patel, Hiral Kotadiya, and Avani R. Vasant

Abstract—The COVID-19 pandemic has led to an increase in digitization. With the strict social and physical distancing measures in place, new routines require accessing the internet for most online services which have led to the explosive growth of data. As a consequence, data mining technologies are used for the extraction of useful information from a huge compilation of such digital data. Thus, the desire to mine data from varied sources to discover behaviors and patterns among entities such as customers, diseases, and environmental conditions is on the rise which can be accomplished by association rule mining. However, such pattern discovery by association rule mining also discloses the personal information of an individual or organization. Thus, the challenge of association rule mining is privacy preservation wherein confidentiality of sensitive rules should be maintained while releasing the database of third parties. Privacy-preserving association rule mining is the process of modifying the original database to hide the sensitive rules for preserving privacy. Thus, the paper emphasizes multiple objectives like minimizing the side effects of hiding sensitive rules. i.e. reduce the number of ghost rules, lost rules, and hiding failure along with the increase in utility of the data.

Index Terms—Data mining, association rule mining, privacy-preserving association rule mining, evolutionary algorithm, genetic algorithm.

Darshana H. Patel is with the I. T. Department, V. V. P. Engineering College, Rajkot, India (e-mail: Hiral Kotadiya is with Weboccult Technologies at Ahmedabad, Gujarat, India. Avani R. Vasant is with Babaria Institute of Technology, Vadodara, Gujarat, India.


Cite:Darshana H. Patel, Hiral Kotadiya, and Avani R. Vasant, "Privacy-Preserving Association Rule Mining Considering Multi-objective through an Evolutionary Algorithm ," International Journal of Computer Theory and Engineering vol. 14, no. 1, pp. 1-8, 2022.

Copyright © 2022 by the authors. 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 (CC BY 4.0).

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