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Advanced Security Model for Detecting Frauds in ATM Transaction
Author(s) -
Vivek V. Jog,
Nilesh R. Pardeshi
Publication year - 2014
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/16674-6679
Subject(s) - computer science , database transaction , computer security , database
card fraud is causing billions of dollars in losses for the card payment industry. In today's world the most accepted payment mode is Debit card for both online and also for regular purchasing; hence frauds related with it are also growing. To find the fraudulent transaction, we implement an Advanced Security Model for ATM payment using Hidden Markov Model (HMM), which detects the fraud by using customers spending behavior. This Security Model is primarily focusing on the normal spending behavior of a cardholder and some advanced securities such as Location, Amount, Time and Sequence of transactions. If the trained Security model identifies any misbehavior in upcoming transaction, then that transaction is permanently blocked until the user enter High Security Alert Password (HSAP). This paper provides an overview of frauds and begins with ATM card statistics and the definition of ATM card fraud. The main outcome of the paper is to find the fraudulent transaction and avoids the fraud before it happens.

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