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Invariant Diversity as a Proactive Fraud Detection Mechanism for Online Merchants | IEEE Conference Publication | IEEE Xplore

Invariant Diversity as a Proactive Fraud Detection Mechanism for Online Merchants


Abstract:

Online merchants face difficulties in using existing card fraud detection algorithms, so in this paper we propose a novel proactive fraud detection model using what we ca...Show More

Abstract:

Online merchants face difficulties in using existing card fraud detection algorithms, so in this paper we propose a novel proactive fraud detection model using what we call invariant diversity to reveal patterns among attributes of the devices (computers or smartphones) that are used in conducting the transactions. The model generates a regression function from a diversity index of various attribute combinations, and use it to detect anomalies inherent in certain fraudulent transactions. This approach allows for proactive fraud detection using a relatively small number of unsupervised transactions and is resistant to fraudsters' device obfuscation attempt. We tested our system successfully on real online merchant transactions and it managed to find several instances of previously undetected fraudulent transactions.
Date of Conference: 04-08 December 2017
Date Added to IEEE Xplore: 15 January 2018
ISBN Information:
Conference Location: Singapore

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