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Detection fraudulent of credit card application using payment gateway.

INTRODUCTION

Credit-card-based purchases can be categorized into two types: 1) physical card and 2) virtual card. In a physical-card based attain, the cardholder presents his card physically to a merchant for making a payment. To bring out fraudulent transactions in this type of purchase, an attacker has to steal the credit card. If the cardholder does not recognize the loss of card, it can guide to a substantial financial failure to the credit card company. In the second type of purchase, only some important information about a card (card number, expiration date, secure code) is mandatory to make the payment. Such purchases are normally completed on the Internet or over the telephone. To consign fraud in these types of purchases, a fraudster basically needs to know the card details. Most of the time, the actual cardholder is not aware that someone else has seen or stolen his card information. The only way to detect this type of fraud is to analyze the spending patterns on every card and to figure out any inconsistency with respect to the "usual" spending patterns. Fraud detection based on the investigation of existing purchase data of cardholder is a promising way to reduce the rate of successful credit card frauds. Since humans tend to exhibit specific behaviorist profiles, every cardholder can be represented by a set of patterns containing information about the typical purchase group, the time since the last purchase, the amount of money used, etc. Deviation from such patterns is a potential threat to the system.

II. Previous Work:

Most of above researches concentrate on protocols of e-commerce and model checking of such transaction properties as atomicity, but the validations of protocols are not sufficient to ensure the integrity and reliability of e-commerce systems because there are still many defects and logic errors at the design level of business processes, which can be exploited by malicious clients. Business processes belong to the application level, and is a rather important part in an online shopping system. They include the business scenarios and applications. Many malicious behaviors in online shopping systems are exploited in business processes.

Additionally, the method of model checking cannot be understood easily by system designers and evaluators as it lacks an intuitive method of graphical modeling. In order to rapidly implement new processes, research on the compliance of cross-organizational processes and their changes is performed. Most of them focus on the security properties like Access Control and Confidential Information in enterprise business processes, and ensure the security of secret and sensible information that cannot be leaked to other parties.

However, online shopping systems have their own security properties such as Atomicity and Payment Completion Invariant Hybrid web applications that combine the APIs of multiple web services into integrated services like online shopping websites have rapidly developed, and caused new security concerns. The web programming model is already under threat from malicious web clients who exploit logic flaws caused by improper distribution of the application functionality between a client and server. Even if the security requirements of enterprise business processes are met, an online shopping business process may not be flawless, and malicious users can obtain additional benefits through a series of actions. Many accidents of existing online shopping systems are caused by data errors and state inconsistency as exploited by malevolent users. Thus, both data properties and data state nondeterminacy must be depicted.

The security analysis from the adversary's perspective has been increasingly important in protocols, intrusion detection systems, and security testing. At the requirement analysis and design levels, one can identify how the software can be attacked by malicious users. According to this idea, misuse or abuse cases and threat modeling are studied. The threat driven system design derives system models from use and misuse cases, and evaluates whether they could mitigate the misuse threats. The threat modeling approach provides a structured way to design secure software systems, but due to the informal nature, most of the current threat modelling approach does not support the verification of threat models.

III. Problem Statement:

The fraud is detected after the fraud is done, the fraud is detected after the complaint of the card holder. The card holder faced a lot of trouble before the investigation close. And also as all the transaction is maintained in a log, we want to retain a huge data. And also now a day's lot of online purchase are made so we don't know the person how is using the card online, we just confine the IP address for authentication purpose. So there need a help from the cyber-crime to investigate the fraud. To pass up the entire above disadvantage we propose the system to detect the fraud in a best and easy way.

IV. System Architecture:

V. Proposed System:

To examine the payment using PayPal and Banking gateway. Using PayPal gateway to secure the third party interaction. In Pay Pal Gateway we demonstrate transaction using real time Personal and Business Accounts. In Banking gateway we demonstrate asymmetric key for protection. By using RSA algorithm to Detection of fraud using credit Limit in Banking Gateway. Using these gateway we protect from Phishing attack.

A. Login:

The customer gives there information to enroll a new card. The information is all about there contact details. They can generate there own login and password for there future use of the card.

In Login Form presents site visitors with a form with username and password fields. If the user enters a suitable username/password combination they will be granted access to additional assets on website. Which additional resources they will have access to can be configured separately.

B. Security information:

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 query where the user has to answer the correctly to move to the transaction sector. It includes 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.

C. 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 begins a credit card transaction by communicating to a credit card number, and storing therein, a distinctive piece of information that characterizes a specific transaction to be made by an authorized user of the credit card at subsequently. The information is allowed as "network data" in the data base only if a correct personal identification code (PIC) is used with the communication. The "network data" will provide to later authorize that specific transaction. Because the transaction is pre-authorized, the vendor does not require to see or transmit a PIC.

For computing the key values using the following asymmetric cryptographic algorithm(i.e) Rivest Shamir & Adleman Algorithm.

Rsa Algorithm:

RSA is an algorithm used by modern computers to encryption and decryption. It is an asymmetric cryptographic algorithm. Asymmetric means that there are two alternate keys. This is also called public key cryptography, for the reason that one of them can be given to everyone.

The RSA algorithm involves four steps:

1. key generation 2. key distribution,

3. encryption 4. decryption.

RSA involves a public key and a private key. The public key can be identified by everyone and is used for encrypting messages. The objective is that messages encrypted with the public key can only be decrypted in a reasonable amount of time using the private key.

The basic principle behind RSA is the examination that it is practical to find three very large positive integers e, d and n such that with modular exponentiation for all m and that even knowing e and n or even m it can be extremely difficult to find d.

1)Key generation:

The keys for the RSA algorithm are created by the following way:

Step 1. Choose two distinct prime numbers p and q.

For security purposes, the integers p and q should be chosen at random, and should be similar in magnitude but 'differ in length by a few digits to make factoring harder. Prime integers can be efficiently originate using a primality test.

Step 2. Compute n = pq.

n is used as the modulus for both the public and private keys. Its length, usually expressed in bits, is the key length.

Step 3. Compute [phi](n) = [phi](p)[phi](q) = (p - 1)(q - 1) = n - (p + q - 1), where [phi] is Euler's totient function. This value is reserved private.

Step 4. Choose an integer e such that 1< e < [phi](n).

Step 5. Determine d as d [equivalent to] [e.sup.-1] (mod [phi](n)); i.e., d is the modular multiplicative inverse of e (modulo y(n)). This is more clearly stated as: solve for d given d x e [equivalent to] 1 (mod y(n)). e is released as the public key exponent. d is kept as the private key exponent.

The public key consists of the modulus n and the public (or encryption) exponent e. The private key consists the modulus n and the private (or decryption) exponent d, which must be set aside secret. p, q, and [phi](n) must also be set aside secret because they can be used to calculate d.

2) Key distribution:

To enable B to send his encrypted messages, A transmits her public key (n, e) to B via a reliable, but not essentially secret way. The private key d is never distributed.

3) Encryption:

Suppose that B would like to send message M to A.

B first turns M into an digit m, 0 [less than or equal to] m < n

and gcd(m, n) = 1 by means of an agreed-upon reversible protocol known as a padding scheme. B then computes the ciphertext c, using A's public key e.

4) Decryption:

A can retrieve m from c by using her private key exponent d by computing.

Given m, B can recover the original message M by reversing the padding scheme.

D. Verification:

Verification information is provided with respect to a transaction between an initiating party and a verification-seeking party, the confirmation information being given by a third, verifying party, based on private information in the possession of the initiating party. In verification the method will seeks card number and if the card number is correct the relevant process will be executed. If the amount is wrong, mail will be sent to the user saying the card no has been block and he can't do the further transaction.

Conclusion:

An application to be proposed in credit card fraud detection. The various steps in credit card transaction processing are represented as the underlying stochastic process. To be used the ranges of transaction amount as the observation symbols, whereas the kind of item have been considered to be states. To suggest a method for finding the spending profile of cardholders, as well as application of this understanding in deciding the value of observation symbols and initial estimate of the model parameters. It has also been explained how this method can detect whether an incoming transaction is fraudulent or not. Experimental results explain the performance and effectiveness of our system and demonstrate the usefulness of learning the spending profile of the cardholders. Comparative studies expose that the Accuracy of the system is close to 80 percent over a wide variation in the input data. The system is as well scalable for handling large volumes of transactions.

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(1) A. Priyangaa, (2) A. Owaiseahmed, (3) A. Kumaresan, (4) K. Vijayakumar

(1,2,3,4) Department of Computer Science and Engineering, SKP Engineering College, Tiruvannamaiai.

Received 28 January 2017; Accepted 22 March 2017; Available online 28 April 2017

Address For Correspondence:

A. Priyangaa, Department of Computer Science and Engineering, SKP Engineering College, Tiruvannamalai.

E-mail: apriyangaa32@gmail.com
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Author:Priyangaa, A.; Owaiseahmed, A.; Kumaresan, A.; Vijayakumar, K.
Publication:Advances in Natural and Applied Sciences
Article Type:Report
Date:Apr 30, 2017
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