Enhancing Fraud Detection in Multi-Participant E-Commerce Transactions Using a Multi-Perspective Approach

Kondanna Kanamaneni, Sushma Pilli, Pavithra Pichili, Pavani Marachi, Sai Teja Akula

2025

Abstract

In the domain of web-based business, where exchanges include numerous members like purchasers, merchants, and go-betweens, the discovery of fake exercises presents a huge test. To resolve this issue, our proposed technique centers around a multi-point-of-view approach pointed toward improving extortion discovery precision and effectiveness. The initial step includes the identification of client ways of behaving, wherein we influence different strategies, for example, conducting investigation and assessment of exchange accounts to acquire experiences into typical client ways of behaving. By understanding common client communications inside the online business environment, we lay out a standard against which strange ways of behaving can be distinguished. Thus, we dig into the investigation of anomalies for include extraction. Using refined peculiarity location calculations, we investigate exchange information to reveal sporadic examples characteristic of possibly deceitful exercises. This interaction permits us to separate significant elements that act as key markers for extortion location. At long last, we utilize a troupe order model to carry out our extortion recognition system, keeping away from dependence on a particular calculation. All things being equal, we influence the qualities of outfit calculations, for example, Irregular Woods, Inclination Helping, or AdaBoost. By taking care of the separated highlights into the group model, we train it to observe among real and fake ways of behaving in multiparticipant online business exchanges. Troupe techniques are especially appropriate for this errand because of their capacity to deal with high-layered information and catch complex choice limits through the blend of assorted base models.

Paper Citation

in Harvard Style

Kanamaneni K., Pilli S., Pichili P., Marachi P. and Akula S. (2025). Enhancing Fraud Detection in Multi-Participant E-Commerce Transactions Using a Multi-Perspective Approach. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 1: ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 760-769. DOI: 10.5220/0013872500004919

in Bibtex Style

@conference{icrdicct`2525,
author={Kondanna Kanamaneni and Sushma Pilli and Pavithra Pichili and Pavani Marachi and Sai Akula},
title={Enhancing Fraud Detection in Multi-Participant E-Commerce Transactions Using a Multi-Perspective Approach},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 1: ICRDICCT`25},
year={2025},
pages={760-769},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013872500004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 1: ICRDICCT`25
TI - Enhancing Fraud Detection in Multi-Participant E-Commerce Transactions Using a Multi-Perspective Approach
SN - 978-989-758-777-1
AU - Kanamaneni K.
AU - Pilli S.
AU - Pichili P.
AU - Marachi P.
AU - Akula S.
PY - 2025
SP - 760
EP - 769
DO - 10.5220/0013872500004919
PB - SciTePress