Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Adhisekar, Kamalakkannan; Mulla, Gulnar Sadat; Thirumalaikumari, T.; Vanitha, P.; Kamepalli, Sujatha; Acharjee, Purnendu Bikash Title A name given to the resource An Intelligent Method for Fraud Detection in Digital Payments based on SVR with GC-RF Approach Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 International Conference on Intelligent Computing and Knowledge Extraction, ICICKE 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICICKE65317.2025.11136358" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICICKE65317.2025.11136358</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105022297396?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105022297396?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Adhisekar K., Department of Corporate Secretaryship &amp; 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 Description An account of the resource 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. Subject The topic of the resource digital transformation; fraud detection (FD); grey catastrophe point (GC); support vector regression Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833153681-7; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online