E-Transactional Fraud Detection Using Fuzzy Association Rule Mining

6 Pages Posted: 6 Jan 2020

See all articles by S Md S Askari

S Md S Askari

Rajiv Gandhi University - Department of Computer Science and Engineering

Md. Anwar Hussain

Rajiv Gandhi University

Date Written: January 1, 2020

Abstract

As the E-transactions have become integral part day-to-day life activities. Hence trust and security has become most crucial part of the financial institutions. We have proposed here fraud detection algorithm for E-transactional frauds. We used here fuzzy logic and Association Rule mining. The fuzzy logic is used to determine the cognitive properties of features, so that the authentic users are not blocked for e-transactions and fraudsters are not allowed and the association rules, we have used to filter out the fraud transactions from the dataset of financial transactions. The results obtained here and the analysis of the results shows that detection rate is high and efficient compared to the other recent works.

Keywords: Fuzzy-ID3, Decision Tree, Information Content, information gain

Suggested Citation

S Askari, S Md and Anwar Hussain, Md., E-Transactional Fraud Detection Using Fuzzy Association Rule Mining (January 1, 2020). Proceedings of the 2nd International Conference on Information Systems & Management Science (ISMS) 2019 | Tripura University, Agartala, Tripura, India, Available at SSRN: https://ssrn.com/abstract=3512408 or http://dx.doi.org/10.2139/ssrn.3512408

S Md S Askari (Contact Author)

Rajiv Gandhi University - Department of Computer Science and Engineering ( email )

Rono Hills
Doimukh
Itanagar, Arunachal Pradesh 791 112
India

Md. Anwar Hussain

Rajiv Gandhi University ( email )

Rono Hills
Doimukh
Itanagar, Arunachal Pradesh 791 112
India

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