ItemConference Paper

An Intelligent Method for Fraud Detection in Digital Payments based on SVR with GC-RF Approach

Title
An Intelligent Method for Fraud Detection in Digital Payments based on SVR with GC-RF Approach
Creator
Adhisekar, Kamalakkannan; Mulla, Gulnar Sadat; Thirumalaikumari, T.; Vanitha, P.; Kamepalli, Sujatha; Acharjee, Purnendu Bikash
Description
The use of automated algorithms to detect fraud on electronic payment networks is challenging. Digital payment systems and their users are vulnerable to cybercriminals who take advantage of security holes or users' negligence to steal passwords, perpetrate fraud, launder money, and carry out other malicious acts. Conventional methods of fraud detection are challenging to execute because of the difficulties of acquiring massive volumes of manually annotated data. It is tough to notice new trends because fraudsters are often changing their techniques. Feature extraction, model training, and data preprocessing were the main areas of emphasis in this systematic research. Data pretreatment encompassed tasks such as acquiring training sample data, cleaning, converting, integrating, and altering the data. Feature extraction is the backbone of SVR-GC-RF model training; it takes all the data in a dataset and turns it into features. The suggested method outperformed SVR and RF in terms of accuracy by 95.23 percent. The importance of hierarchical fraud detection in online payment systems is highlighted in this paper. Through the use of effective feature extraction and model training, the study enhances fraud detection. Methods for detecting fraud need to change if they are to keep up with the criminals. 2025 IEEE.
Source
2025 International Conference on Intelligent Computing and Knowledge Extraction, ICICKE 2025;
Date
01-01-2025
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
digital transformation; fraud detection (FD); grey catastrophe point (GC); support vector regression
Coverage
Adhisekar K., Department of Corporate Secretaryship & Accounting and Finance, Faculty of Science and Humanities, SRM Institute of Science and Technology, Kattankulathur, India; Mulla G.S., University of Technology Bahrain Salmabad, Bahrain; Thirumalaikumari T., Department of Computer Science, Saveetha College of Liberal Arts and Sciences, Saveetha Institute of Medical and Technical Science, Chennai, India; Vanitha P., Department of Management Studies, M. Kumarasamy College of Engineering, Karur, India; Kamepalli S., Department of Information Technology, Vignan's Foundation for Science Technology and Research, Guntur, India; Acharjee P.B., Department of Computer Science, CHRIST University, Bangalore, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-833153681-7;
Format
online
Language
English
Type
Conference paper

Citation

Adhisekar, Kamalakkannan; Mulla, Gulnar Sadat; Thirumalaikumari, T.; Vanitha, P.; Kamepalli, Sujatha; Acharjee, Purnendu Bikash, “An Intelligent Method for Fraud Detection in Digital Payments based on SVR with GC-RF Approach,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/26013.

Output Formats