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E-Transactional Fraud Detection Using Fuzzy Association Rule Mining

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Document pages: 6 pages

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.

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