ItemConference Paper

A Novel Network-Based Digital Payment Fraud Detection using OP-ELM Network

Title
A Novel Network-Based Digital Payment Fraud Detection using OP-ELM Network
Creator
Sandeep, C.S.; Yadav, Sameer; Kumar, B. Rajesh; Baranidharan, S.; Vijayaraj, T.; Lakineni, Prasanna Kumar
Description
Internet and Industry 4.0 have helped banks and other financial organizations enhance procedures and decrease fraud. Digital payment techniques have helped internet buying skyrocket. Industry 4.0 promotes process optimization, ecosystem collaboration, and growth by integrating digital systems with physical and IoT devices. Unfortunately, digital payment cybercrime has grown rapidly, causing large annual financial losses. Because of this, fraud detection systems must be constantly improved. The suggested TLELM approach includes preprocessing, feature selection, and model training. Preprocessing involves standardizing data, eliminating outliers, and handling null or missing values. The CSO technique selects relevant features by optimizing selection. A new approach combining TL and ELM improves DPFD procedures. The new metaheuristic TL excels at combinatorial optimization. TLELM efficacy was examined using multiple datasets. The recommended method was compared to top-tier algorithms for binary and multiclass data categorization. Experimental data shows that TLELM outperforms other models with 99.37% accuracy. This study found that TLELM can detect online payment fraud. The method optimizes fraud detection and classification accuracy using TL and ELM. Add more real-world datasets to strengthen robustness and make additional improvements to handle future fraud methods. 2025 IEEE.
Source
3rd International Conference on Data Science and Information System, ICDSIS 2025;
Date
01-01-2025
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
competitive swarm optimization (CSO); digital payment fraud detection (DPFD); extreme learning machine (ELM); single layer feedforward neural network (SLFN); transformer learning (TL)
Coverage
Sandeep C.S., Jawaharlal College of Engineering and Technology, Department of Electronics and Communication Engineering, Palakkad, India; Yadav S., University of Allahabad, Department of Commerce and Business Administration, Prayagraj, India; Kumar B.R., Dhanalakshmi Srinivasan College of Engineering, Department of Computer Science and Engineering, Coimbatore, India; Baranidharan S., Christ University, School of Business and Management, Bangalore, India; Vijayaraj T., Prince Shri Venkateshwara Padmavathy Engineering College, Department of Mechanical Engineering, Chennai, India; Lakineni P.K., Koneru Lakshmaiah Education Foundation, Department of Computer Science and Engineering, Vaddeswaram, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-833154265-8;
Format
online
Language
English
Type
Conference paper

Citation

Sandeep, C.S.; Yadav, Sameer; Kumar, B. Rajesh; Baranidharan, S.; Vijayaraj, T.; Lakineni, Prasanna Kumar, “A Novel Network-Based Digital Payment Fraud Detection using OP-ELM Network,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/25972.

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