Credit Card Fraud Detection
Abstract
Now a day the usage of
credit cards has dramatically increased. As credit card becomes the most
popular mode of payment for both online as well as regular purchase, cases of
fraud associated with it are also rising. In this paper, we model the sequence
of operations in credit card transaction processing using a Hidden Markov Model
(HMM) and show how it can be used for the detection of frauds. An HMM is
initially trained with the normal behavior of a cardholder.
If an incoming credit
card transaction is not accepted by the trained HMM with sufficiently high
probability, it is considered to be fraudulent. At the same time, we try to
ensure that genuine transactions are not rejected. We present detailed
experimental results to show the effectiveness of our approach and compare it
with other techniques available in the literature.
Existing System:
In case of the existing
system the fraud is detected after the fraud is done that is, the fraud is
detected after the complaint of the card holder. And so the card holder faced a
lot of trouble before the investigation finish. And also as all the transaction
is maintained in a log, we need to maintain a huge data.
And also now a days lot of online purchase are
made so we don’t know the person how is using the card online, we just capture
the IP address for verification purpose. So there need a help from the cybercrime
to investigate the fraud. To avoid the entire above disadvantage we propose the
system to detect the fraud in a best and easy way.
Proposed System:
In
proposed system, we present a Hidden Markov Model (HMM).Which does not require
fraud signatures and yet is able to detect frauds by considering a cardholder’s
spending habit. Card transaction processing sequence by the stochastic process of an HMM.
The details of items
purchased in Individual transactions are usually not known to an FDS running at
the bank that issues credit cards to the cardholders. Hence, we feel that HMM
is an ideal choice for addressing this problem. Another important advantage of
the HMM-based approach is a drastic reduction in the number of False Positives
transactions identified as malicious by an FDS although they are actually
genuine.
An FDS runs at a credit
card issuing bank. Each incoming transaction is submitted to the FDS for
verification. FDS receives the card details and the value of purchase to
verify, whether the transaction is genuine or not. The types of goods that are
bought in that transaction are not known to the FDS. It tries to find any
anomaly in the transaction based on the spending profile of the cardholder,
shipping address, and billing address, etc.
Advantage:
1.
The detection of the fraud use of the card is found much faster that the
existing system.
2. In case of the existing system
even the original card holder is also checked for fraud detection. But in this system no need to check the original user as we
maintain a log.
3. The log which is maintained will
also be a proof for the bank for the transaction made.
4. We can find the most accurate
detection using this technique.
5. This reduce the tedious work of
an employee in the bank
Applications:
1. Speech recognition Applications
2. Bioinformatics Applications
3. Genomics Applications
Modules
1. New card
2. Login
3. Security information
4. Transaction
5. Verification
Module Description
1. New
card
In this module, the
customer gives there information to enroll a new card. The information is all
about their contact details. They can create their own login and password for their
future use of the card.
2. Login
In Login Form module
presents site visitors with a form with username and password fields. If the
user enters a valid username/password combination they will be granted access
to additional resources on website. Which additional resources they will have
access to can be configured separately.
3.
Security information
In Security information
module it will get the information detail and its store’s in database. If the card lost then the Security
information module form arise. It has a set of question where the user has to
answer the correctly to move to the transaction section.
It contain informational privacy and
informational self-determination are addressed squarely by the invention
affording persons and entities a trusted means to user, secure, search,
process, and exchange personal and/or confidential information.
4.
Transaction
The method and apparatus
for pre-authorizing transactions includes providing a communications device to
a vendor and a credit card owner. The credit card owner initiates a credit card
transaction by communicating to a credit card number, and storing therein, a
distinguishing piece of information that characterizes a specific transaction
to be made by an authorized user of the credit card at a later time.
The information is
accepted as "network data" in the data base only if a correct
personal identification code (PIC) is used with the communication. The
"network data" will serve to later authorize that specific
transaction. The credit card owner or other authorized user can then only make
that specific transaction with the credit card. Because the transaction is
pre-authorized, the vendor does not need to see or transmit a PIC.
5.Verification
Verification
information is provided with respect to a transaction between an initiating
party and a verification-seeking party, the verification information being
given by a third, verifying party, based on confidential information in the
possession of the initiating party. In verification the process will seeks card
number and if the card number is correct the relevant process will be executed.
If the number is wrong, mail will be sent to the user saying the card no has
been block and he can’t do the further transaction.
Hardware Requirements
• SYSTEM : Pentium IV 2.4 GHz
• HARD DISK :
40 GB
• FLOPPY DRIVE :
1.44 MB
• MONITOR : 15 VGA color
• MOUSE : Logitech
• RAM : 256 MB
Software Requirements
• Operating system :
Windows XP Professional
• Front End : Asp .Net 2.0
• Coding Language :
Visual C# .Net
• Back-End : Sql
Server 2005.
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