Fraudulent Detection System Using Hidden Markov Model

Author(s):

Shivam Srivastav , Bharati Vidyapeeth College of Engineering, Pune; Dr. Suhas Patil, Bharati Vidyapeeth College of Engineering, Pune; Pratap Singh, Bharati Vidyapeeth College of Engineering, Pune; Naman Sharma, Bharati Vidyapeeth College of Engineering, Pune

Keywords:

Hidden Markov Model, HMM, fraud transaction, credit card, credit card frauds, OTP

Abstract:

In light of recent events, including the Coronavirus pandemic, the most accepted mode of shopping and purchasing goods and services is online through credit card. It provides cashless shopping at every possible shop in all countries and will be the most easy way to do online shopping, paying bills, requesting services etc. for years to come. With that said, credit card frauds are increasing day by day as well, regardless of the various techniques developed for its detection. Fraudsters are so expert that they engineer new ways for committing fraudulent transactions everyday which demands for constant innovation for its detection techniques also. Many techniques based on Artificial Intelligence, Data mining, Fuzzy logic, Machine learning, Sequence Alignment, decision tree, neural network, logistic regression, naïve Bayesian, Bayesian network, meta-learning, Genetic Programming etc., has evolved in detecting various credit card fraudulent transactions. In this paper, Hidden Markov Model (HMM) is employed to model the sequence of operation in credit card transaction operations. It helps to get a high fraud coverage combined with an exceptionally low false alarm rate.`

Other Details:

Manuscript Id	:	IJSTEV8I1009
Published in	:	Volume : 8, Issue : 1
Publication Date	:	01/08/2021
Page(s)	:	6-11

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