Methodology of Fraud and Theft Detection using Data Mining

NIT6130 INTRODUCTION TO RESEARCH
ASSIGNMENT 3 – METHODOLOGY
by
Rachid Hamadi
Student ID: 30099999

Table of Contents
Table of Contents.................................................................................................................................ii
Chapter 1 Methodology........................................................................................................................1
1.1 Research Problem and Reorganized Collected Literature..........................................................1
1.1.1 Research Problem Statement...............................................................................................1
1.1.2 Reorganized Collected Literature........................................................................................2
1.2 Types of Methodology...............................................................................................................3
1.2.1 Qualitative and Quantitative Methodologies.......................................................................3
1.2.2 Type of Chosen Methodology.............................................................................................3
1.3 Review of the Existing Methodologies......................................................................................4
1.3.1 Selected Sub-Problem.........................................................................................................4
1.3.2 Analysis of the Selected Methodologies.............................................................................4
1.3.3 Relevance of the Research Problem....................................................................................6
1.3.4 Summary of the Reviewed Methodologies.........................................................................6
1.4 Proposed Methodology...............................................................................................................6
1.4.1 Identification and Justification............................................................................................6
1.4.2 Benefits and Limitations.....................................................................................................7
1.4.3 Framework and Explanation...............................................................................................8
List of References...............................................................................................................................10
ii

Chapter 1
Methodology
This assignment focuses on the methodology of fraud and theft detection using data mining.
Fraud has been one of the greatest challenges for business organizations. This assignment deals
with the methodology followed in the study of fraud detection by data mining process.
1.1 Research Problem and Reorganized Collected Literature
1.1.1 Research Problem Statement
The enhancement of the technology have been helping in maintaining a proper data transfer
over the network. Identity crime has been one if the major fraud and theft cases in the
organizations. Fraud cases have been increasing all over the world due to the enhancement of
technology. The negative use of the technology have been creating chances for hackers to
breach into various networks for taking data form it (Odetola et al. 2018). The data theft have
been increasing over the network. Cloning has been another problem faced by the organizations
and users. These acts have been performed in credit cards and passports cloning. Data and
information regarding credit card credentials and fake passports have been created in the
market. Fraud behavior of any person need to be detected in the organizations. Fraud has been
an intentional theft act performed by any person in an organization or in the society. It has been
referred to abuse of profit of an organization in legal platform.
1

1.1.2 Reorganized Collected Literature
Research
Problem
Sub-problem Collected Literature
Skimming Financial fraud Agrawal, S. and Agrawal, J., 2015.
survey on anomaly detection using
data mining techniques. Procedia
Computer Science, 60, pp.708-713.
Save, P., Tiwarekar, P., Jain, K.N. and
Mahyavanshi, N., 2017. A novel idea
for credit card fraud detection using
decision tree. International Journal of
Computer Applications, 161(13).
Application fraud Tran, P.H., Tran, K.P., Huong, T.T., Heuchenne, C.,
HienTran, P. and Le, T.M.H., 2018, February. Real
Time Data-Driven Approaches for Credit Card
Fraud Detection. In Proceedings of the 2018
International Conference on E-Business and
Applications (pp. 6-9). ACM.
... Mahmoudi, N. and Duman, E., 2015. Detecting
credit card fraud by modified Fisher discriminant
analysis. Expert Systems with Applications, 42(5),
pp.2510-2516.
Cloning Identity theft Prabakaran, S. and Mitra, S., 2018, April. Survey of
Analysis of Crime Detection Techniques Using
Data Mining and Machine Learning. In Journal of
Physics: Conference Series (Vol. 1000, No. 1, p.
012046). IOP Publishing.
...
2