Title
Feature Extraction for Fraud Detection in Electronic Marketplaces
Abstract
Electronic markets are software systems that enable online transactions between buyers and sellers. One of the major challenges in these markets is to establish the notion of trust among users. This is normally addressed by introducing a reputation system that allows users to be evaluated for each transaction they perform. This work considers the problem of detecting fraudulent behavior of users against reputation systems in Electronic Marketplaces. We select and exhibit seventeen features with good discrimination power that are effective for this task, and we conducted experiments using data from a real-world dataset from a large Brazilian marketplace, including a list of known fraudsters identified by fraud experts. As a quick and first application of these features, we find out how a minimal number of features k could be used as a stronger evidence of fraud. With k = 1 we cover as much as 97% of known frauds, but the precision is only 14.31% (F-measure 0.25). The best F-measure is 0.43 and occurs for k = 4 and k = 5. Since many sellers who fraud the reputation system are still undetected, the computed precisions are not reliable. Almost all supposed false positives with at least ten features were manually checked and confirmed by experts to have fraudulent behavior, changing precision from 47% to at least 98%, for k = 10. At the end, the fraudster list was increased by 32% by this first analysis and the largest reviewed F-measure is 0.60.
Year
DOI
Venue
2009
10.1109/LA-WEB.2009.20
Merida, Yucatan
Keywords
Field
DocType
software system,best f-measure,electronic marketplaces,fraud detection,known fraud,fraudster list,reputation system,features k,fraudulent behavior,feature extraction,known fraudsters,fraud expert,computed precision,software systems,human factors,transaction processing,false positive,data mining,electronic commerce,e commerce,e business,behavior change
Transaction processing,Data mining,Electronic business,Reputation system,Information retrieval,Computer science,Software system,Database transaction,E-commerce,False positive paradox,Reputation
Conference
ISBN
Citations 
PageRank 
978-0-7695-3856-3
4
0.47
References 
Authors
19
4
Name
Order
Citations
PageRank
Rafael Maranzato1191.15
Marden Neubert210010.09
Adriano M. Pereira39721.73
Alair Pereira Do Lago410610.10