International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Science , Computer Science and Engineering

Volume3,January 2016,

Topic : Credit And Debit Card Transaction Survey Using Map Reduce In Hdfs And Implementing Syferlock To Prevent Fraudulent

Authors:R.Anbuvizhi || V.Balakumar

Abstract:Big Data” is a term that has jumped overnight from its roots. It can be described as an innovative technique and technology to save, distribute, manage, visualize and analyze larger-sized data with extreme velocity and methods to manage unstructured and structure incapable amount of data. Nowadays fraud transactions in real time are increasing, so identifying large-scale patterns across many transactions or detecting anomalous behavior from an individual user can change the fraudulent in online transaction. Thus banks are turning to analytics to predict and prevent fraud in real times. In this project, proposed system deals with Credit and Debit card management to improve its scalability and efficiency in big data environment, it is implemented on (HDFS) Hadoop distributed file system. On the other hand, nowadays fraudulent and web attacker are increased to steel the password. In order to overcome those, proposed system implements SyferLock concept to add more security to Credit card transaction. The changes include a stronger user authentication tool, SyferLock that will require associates to follow a few new steps when logging into the network remotely. SyferLock patented, random number generation authentication solutions provide next generation One-Time Passwords/PINs (OTPs) for secure access to computers, networks and the Internet. SyferLock has engineered an enhanced authentication methodology and system using device-less OTPs that provides users with a simple, more secure way to access information leveraging their existing passwords. It uses a one-time password that expired once used. This added security strengthens the ability to protect the applications and systems..

Keywords: Analysis, Big Data, Credit Card, GridPin, Hadoop, Map Reduce, Report, Security, Syferlock

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DOI: 01.1617/vol3iss1pid137

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Dr. Allon Guez
Professor, Drexel University,

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Thomson Reuters ID : q-6288-2016.
ORCiD Research ID : 0000-0001-9540-6799

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Journal Code : IJERCSE
Electronic ISSN : 2394-2320
Impact Factor : 4.890
Frequency : monthly
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