A Survey: Methodologies used for Fraud Detection in Digital Transactions

Autor: J Vijaya, Chandana Gouri Tekkali
Rok vydání: 2021
Předmět:
Zdroj: 2021 Second International Conference on Electronics and Sustainable Communication Systems (ICESC).
DOI: 10.1109/icesc51422.2021.9532915
Popis: A Transaction plays a vital role in our daily routine life. It can be done through either Physical or Digital. Mostly people were travelled with digital transactions to make their activities in easy and convenient way in recent days. Digital Transactions are transactions in which the customer authorizes the transfer of money through an electronic mode. Generally Digital Transactions are also called E-Transactions. The main aim of our Indian system is to make India as Digital India. Many technologies were introduced to identify the frauds in E-Transactions. As a result, scams are also having increased alongside. According to information provided by the CERT (Indian Computer Emergency Response Team), the total number of cybercrimes was increased from the years 2018 to 2020 was 1,59,761;2,46,514 and 2,90,445 respectively [1]. Many authors surveyed about classification techniques for detecting frauds like data mining, a Machine Learning. This survey paper has related to how to detect frauds among the transactions with the help of machine learning and deep learning algorithms for a classification and the prediction, which gives more accuracy and works efficiently by considering different datasets. A brief discussion of future research developments is discussed in this article.
Databáze: OpenAIRE