PROPOSAL FOR CREDIT CARD l ASSIGNMENT

Running head: PROPOSAL
Classification Scheme for Credit Card Fraud Detection in Data mining
Name of Student
Name of University
Author Note

1
PROPOSAL
Table of Contents
1. Introduction and Background..........................................................................................2
2. Research Aim...................................................................................................................2
3. Research Objective..........................................................................................................3
4. Resources and Deliverables.............................................................................................3
5. Academic Challenges and Ethical Issues........................................................................4
6. Literature Review............................................................................................................6
6.1. Credit card Fraud and Hacking.................................................................................6
6.2. Data Mining in Detection of Credit card fraud.........................................................7
7. Project Plan (Time Scale)................................................................................................7
References............................................................................................................................9

2
PROPOSAL
Title: Classification Scheme for Credit Card Fraud Detection in Data mining
1. Introduction and Background
Credit Card fraud falls in the category of identity theft and all through the years, there
have been an alarming increase of credit card frauds, mostly because of the increasing
sophistication of the hackers (Seeja and Zareapoor 2014). One of the primary reasons behind the
rampant upsurge in fraud with credit cards in the recent years is mostly because credit cards are
used for majority of the business works, such as to request payment form the different companies
over internet (Dal Pozzolo et al. 2015). Therefore, there is a need to ensure secure transaction
for the credit card owners while making a transaction. The security of the credit card can be
linked with the usage of data mining (Bahnsen et al. 2016). This technology has popularly
gained recognition in managing the credit card frauds by making use of its effective machine
learning algorithms.
The research study is proposed that will evaluate the importance and practice of data
mining technology in detection of frauds using credit cards. The study will mostly focus on the
classification scheme for detection of frauds associated with credit cards (Hegazy Madian and
Ragaie 2016). Currently the technology of data mining is considered to be one of the most
popular way of combating credit card frauds mostly because of its effectiveness in analysis of the
fraud (Bhusari and Patil 2016). Data mining is a technique of classifying a massive amount of
data to extract valuable information even from unstructured data (Matheswaran and Rajesh
2015). Classification scheme in data mining can help in recognizing the patterns of former
fraudulent behavior and therefore, this study is undertaken to evaluate the use of the
classification scheme in data mining in fraud detection.

3
PROPOSAL
2. Research Aim
The report aims to evaluate the usage of data mining in detecting the frauds that are being
conducted with credit cards.
3. Research Objective
The key objectives of the proposed study are indicated as follows-
 To discuss the concept of credit card hacking
 To identify the various ways of credit card hacking
 To examine the application of data mining in detecting frauds using credit cards
 To recommend strategies of reducing credit card frauds by using the technology
of data mining
The successful completion of the study is expected to fulfill the above identified
objectives.
4. Resources and Deliverables
The wide range of secondary resources will be evaluated in the literature review to collect
data from the researches that are already conducted in this field. These resources include
previously published journals, books and literature. The human resources associated with this
research study are indicated below-
1. Researcher
2. Professor and Guide
3. Librarian