TY - GEN
T1 - E-commerce reputation manipulation
T2 - 24th International Conference on World Wide Web, WWW 2015
AU - Xu, Haitao
AU - Liu, Daiping
AU - Wang, Haining
AU - Stavrou, Angelos
PY - 2015/5/18
Y1 - 2015/5/18
N2 - In online markets, a store's reputation is closely tied to its profitability. Sellers' desire to quickly achieve high reputation has fueled a profitable underground business, which operates as a specialized crowdsourcing marketplace and accumulates wealth by allowing online sellers to harness human laborers to conduct fake transactions for improving their stores' reputations. We term such an underground market a seller-reputation-escalation (SRE) market. In this paper, we investigate the impact of the SRE service on reputation escalation by performing in-depth measurements of the prevalence of the SRE service, the business model and market size of SRE markets, and the characteristics of sellers and offered laborers. To this end, we have infiltrated five SRE markets and studied their operations using daily data collection over a continuous period of two months. We identified more than 11,000 online sellers posting at least 219,165 fake-purchase tasks on the five SRE markets. These transactions earned at least 46,438 in revenue for the five SRE markets, and the total value of merchandise involved exceeded 3,452,530. Our study demonstrates that online sellers using SRE service can increase their stores' reputations at least 10 times faster than legitimate ones while only 2.2% of them were detected and penalized. Even worse, we found a newly launched service that can, within a single day, boost a seller's reputation by such a degree that would require a legitimate seller at least a year to accomplish. Finally, armed with our analysis of the operational characteristics of the underground economy, we offer some insights into potential mitigation strategies.
AB - In online markets, a store's reputation is closely tied to its profitability. Sellers' desire to quickly achieve high reputation has fueled a profitable underground business, which operates as a specialized crowdsourcing marketplace and accumulates wealth by allowing online sellers to harness human laborers to conduct fake transactions for improving their stores' reputations. We term such an underground market a seller-reputation-escalation (SRE) market. In this paper, we investigate the impact of the SRE service on reputation escalation by performing in-depth measurements of the prevalence of the SRE service, the business model and market size of SRE markets, and the characteristics of sellers and offered laborers. To this end, we have infiltrated five SRE markets and studied their operations using daily data collection over a continuous period of two months. We identified more than 11,000 online sellers posting at least 219,165 fake-purchase tasks on the five SRE markets. These transactions earned at least 46,438 in revenue for the five SRE markets, and the total value of merchandise involved exceeded 3,452,530. Our study demonstrates that online sellers using SRE service can increase their stores' reputations at least 10 times faster than legitimate ones while only 2.2% of them were detected and penalized. Even worse, we found a newly launched service that can, within a single day, boost a seller's reputation by such a degree that would require a legitimate seller at least a year to accomplish. Finally, armed with our analysis of the operational characteristics of the underground economy, we offer some insights into potential mitigation strategies.
KW - E-Commerce
KW - Fake Transaction
KW - Reputation Manipulation
UR - http://www.scopus.com/inward/record.url?scp=84968920011&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84968920011&partnerID=8YFLogxK
U2 - 10.1145/2736277.2741650
DO - 10.1145/2736277.2741650
M3 - Conference contribution
AN - SCOPUS:84968920011
T3 - WWW 2015 - Proceedings of the 24th International Conference on World Wide Web
SP - 1296
EP - 1306
BT - WWW 2015 - Proceedings of the 24th International Conference on World Wide Web
PB - Association for Computing Machinery, Inc
Y2 - 18 May 2015 through 22 May 2015
ER -