Leveraging Product Characteristics for Online Collusive Detection in Big Data Transactions

doi:10.1109/ACCESS.2019.2891907

CORC > 上海财经大学 > 上海财经大学

	Leveraging Product Characteristics for Online Collusive Detection in Big Data Transactions
	Luo, Suyuan 1,2; Wan, Shaohua 3
刊名	IEEE ACCESS
	2019
卷号	7 页码:40154-40164
关键词	E-business fraud detection reputation system SNA K core
ISSN号	2169-3536
DOI	10.1109/ACCESS.2019.2891907
英文摘要	Online fraud transaction has been a big concern for e-business platform. As the development of big data technology, e-commerce users always evaluate the sellers according to the reputation scores supplied by the platform. The reason why the sellers prefer chasing high reputation scores is that high reputations always bring high profit to sellers. By collusion, fraudsters can acquire high reputation scores and it will attract more potential buyers. It has been a crucial task for the e-commerce website to recognizing the fake reputation information. E-commerce platforms try to solve this continued and growing problem by adopting data mining techniques. With the high development of the Internet of Things, big data plays a crucial role in economic society. Big data brings economic growth in different domains. It supplies support to the management and decision-making ability in e-business through analyzing operational data. In online commerce, the big data technology also helps in providing users with a fair and healthy reputation system, which improves the shopping experience. This paper aims to put forward a conceptual framework to extract the characteristics of fraud transaction, including individual- and transaction-related indicators. It also contains two product features: product type and product nature. The two features obviously enhance the accuracy of fraud detection. A real-world dataset is used to verify the effectiveness of the indicators in the detection model, which is put forward to recognize the fraud transactions from the legitimate ones.
WOS研究方向	Computer Science ; Engineering ; Telecommunications
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000463651700001
内容类型	期刊论文
源URL	[http://10.2.47.112/handle/2XS4QKH4/391]
专题	上海财经大学
通讯作者	Wan, Shaohua
作者单位	1.Shenzhen Univ, Coll Management, Inst Big Data Intelligent Management & Decis, Shenzhen 518060, Peoples R China; 2.Shanghai Univ Finance & Econ, Sch Informat Management & Engn, Shanghai 200433, Peoples R China; 3.Zhongnan Univ Econ & Law, Sch Informat & Safety Engn, Wuhan 430073, Hubei, Peoples R China
推荐引用方式 GB/T 7714	Luo, Suyuan,Wan, Shaohua. Leveraging Product Characteristics for Online Collusive Detection in Big Data Transactions[J]. IEEE ACCESS,2019,7:40154-40164.
APA	Luo, Suyuan,&Wan, Shaohua.(2019).Leveraging Product Characteristics for Online Collusive Detection in Big Data Transactions.IEEE ACCESS,7,40154-40164.
MLA	Luo, Suyuan,et al."Leveraging Product Characteristics for Online Collusive Detection in Big Data Transactions".IEEE ACCESS 7(2019):40154-40164.