NDLI: Fuzzy rule optimization for online auction frauds detection based on genetic algorithm

Content Provider	Springer Nature Link
Author	Yu, Cheng Hsien Lin, Shi Jen
Copyright Year	2013
Abstract	Due to the huge amount of users and low entrance cost of online auction, there are a lot of online fraud cases in online auction sites. According to the IC3 reports from 2003 to 2010, we can understand the fraud cases and victims are increasing rapidly year by year. To improve the prevention of online auction frauds, this research will propose a hybrid approach to detect the fraudster accounts to help the users to identify which seller is more dangerous. In this research, we use social network analysis to produce the behavior features and transform these features into fuzzy rules which can represent the detection rules. Then optimize the fuzzy rules by genetic algorithms to build the auction fraud detection model. For implementation, we collect the real auction data from the online auction site http://www.ruten.com.tw which is the most popular auction site in Taiwan. Finally, we use the proposed features and methodologies to detect the fraudster accounts and find out the detection models of them. We hope the result of this research can help the website administrators to detect the possible collusive fraud groups easier in online auction.
Starting Page	169
Ending Page	182
Page Count	14
File Format	PDF
ISSN	13895753
Journal	Electronic Commerce Research
Volume Number	13
Issue Number	2
e-ISSN	15729362
Language	English
Publisher	Springer US
Publisher Date	2013-04-05
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Online auction Fraud detection Fuzzy rule Social network analysis Genetic algorithm Business Information Systems Data Structures, Cryptology and Information Theory Operations Research/Decision Theory Computer Communication Networks Business/Management Science e-Commerce/e-business
Content Type	Text
Resource Type	Article
Subject	Economics, Econometrics and Finance Human-Computer Interaction

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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