Problem Reduction in Online Payment System Using Hybrid Model

TL;DR

This paper proposes a hybrid model combining Hidden Markov Model and mobile implicit authentication to detect online frauds, aiming to improve accuracy and reduce false positives in online transaction security.

Contribution

It introduces a novel hybrid approach that enhances fraud detection by integrating HMM with mobile implicit authentication, addressing limitations of traditional methods.

Findings

Higher detection accuracy compared to traditional methods

Reduced false positive rate in fraud detection

Enhanced security in online transactions

Abstract

Online auction, shopping, electronic billing etc. all such types of application involves problems of fraudulent transactions. Online fraud occurrence and its detection is one of the challenging fields for web development and online phantom transaction. As no-secure specification of online frauds is in research database, so the techniques to evaluate and stop them are also in study. We are providing an approach with Hidden Markov Model (HMM) and mobile implicit authentication to find whether the user interacting online is a fraud or not. We propose a model based on these approaches to counter the occurred fraud and prevent the loss of the customer. Our technique is more parameterized than traditional approaches and so,chances of detecting legitimate user as a fraud will reduce.