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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM5086
Volume:
4 |
7 |
Jul 2020
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Online auction platforms use a unique business model based on price bidding. Bidders compete by placing higher bids on items, and the highest bidder at the end of the auction wins. Detecting fraud in this system is crucial for maintaining a fair environment. Fraud detection involves binary classification, where machine learning models are trained to differentiate between legitimate and fraudulent bids. By analyzing bid details and historical data, these models can identify suspicious activities and take appropriate actions to ensure the integrity of the auction process. This helps create a trustworthy platform for online auctions, benefiting both buyers and sellers. The advance and secure online auctioning system is a versatile approach for facilitating lot-based online auctioning system. he products will be verified, and the site will provide a secure and safe experience for online users. There are some many existing applications which does not contain some local products and they are not available for bidding.
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Publication Date
5/19/2023
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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