skip to main content
10.1145/2736277.2741650acmotherconferencesArticle/Chapter ViewAbstractPublication PageswwwConference Proceedingsconference-collections
research-article

E-commerce Reputation Manipulation: The Emergence of Reputation-Escalation-as-a-Service

Published:18 May 2015Publication History

ABSTRACT

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.

References

  1. http://en.wikipedia.org/wiki/Taobao.Google ScholarGoogle Scholar
  2. http://blog.ebay.com/ebay-marketplaces-introduces-new-logo/.Google ScholarGoogle Scholar
  3. http://en.wikipedia.org/wiki/Alibaba_Group.Google ScholarGoogle Scholar
  4. http://blogs.wsj.com/chinarealtime/2015/03/03/cat-and-mouse-game-alibaba-exec-on-fake-transactions/Google ScholarGoogle Scholar
  5. http://www.jamaicaobserver.com/business/Alibaba-China-s-Internet-behemoth_17598819.Google ScholarGoogle Scholar
  6. http://www.alexa.com/topsites/global.Google ScholarGoogle Scholar
  7. http://venturebeat.com/2014/03/31/alibaba-plunks-down-692m-to-push-into-offline-retail/.Google ScholarGoogle Scholar
  8. http://www2.88sxy.com/.Google ScholarGoogle Scholar
  9. http://www.ntyjy.com/.Google ScholarGoogle Scholar
  10. http://www.shuazuanshuaxinyu.com/.Google ScholarGoogle Scholar
  11. http://www.kus.cc/Index.html.Google ScholarGoogle Scholar
  12. http://www.shuakewang.com/.Google ScholarGoogle Scholar
  13. http://data.worldbank.org/indicator/NY.GDP.PCAP.CD.Google ScholarGoogle Scholar
  14. http://bbs.tianya.cn/post--law--438844--1.shtml.Google ScholarGoogle Scholar
  15. http://weitao.taobao.com/tzh/feed/feed_detail_display.htm?feedId=100505423&wsnsUid=2054965595.Google ScholarGoogle Scholar
  16. K. Hoffman, D. Zage, and C. Nita--Rotaru. A survey of attack and defense techniques for reputation systems. In ACM Computing Surveys (CSUR), 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. J. Caballero, C. Grier, C. Kreibich, and V. Paxson. Measuring pay--per--install: The commoditization of malware distribution. In Proceedings of the 20th USENIX Security Symposium, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. N. Christin. Traveling the silk road: A measurement analysis of a large anonymous online marketplace. In Proceedings of the 22nd International Conference on World Wide Web (WWW), 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. J. Franklin, V. Paxson, A. Perrig, and S. Savage. An inquiry into the nature and causes of the wealth of internet miscreants. In Proceedings of the 14th ACM Conference on Computer and Communications Security (CCS), 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. K. Levchenko, A. Pitsillidis, N. Chachra, B. Enright, M. Felegyhazi, C. Grier, T. Halvorson, C. Kanich, C. Kreibich, H. Liu, D. McCoy, N. Weaver, V. Paxson, G. M. Voelker, and S. Savage. Click trajectories: End--to--end analysis of the spam value chain. In Proceedings of the 32nd IEEE Symposium on Security and Privacy, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. J. Li, M. Ott, and C. Cardie. Identifying manipulated offerings on review portals. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2013.Google ScholarGoogle Scholar
  22. D. Mayzlin, Y. Dover, and J. Chevalier. Promotional reviews: An empirical investigation of online review manipulation. in National Bureau of Economic Research, No. w18340, 2012.Google ScholarGoogle Scholar
  23. C. Nosko, and S. Tadelis. The limits of reputation in platform markets: An empirical analysis and field experiment. Working paper, 2014Google ScholarGoogle Scholar
  24. C. Dellarocas, and C.A. Wood. The sound of silence in online feedback: Estimating trading risks in the presence of reporting bias. Management Science, 54(3):460--476, 2008 Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. C. Grier, L. Ballard, J. Caballero, N. Chachra, C. J. Dietrich, K. Levchenko, P. Mavrommatis, D. McCoy, A. Nappa, A. Pitsillidis, N. Provos, M. Z. Rafique, M. A. Rajab, C. Rossow, K. Thomas, V. Paxson, S. Savage, and G. M. Voelker. Manufacturing compromise: The emergence of exploit-as-a-service. In Proceedings of the 19th ACM Conference on Computer and Communications Security (CCS), 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. D. McCoy, H. Dharmdasani, C. Kreibich, G. M. Voelker, and S. Savage. Priceless: The role of payments in abuse--advertised goods. In Proceedings of the 19th ACM Conference on Computer and Communications Security (CCS), 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. D. McCoy, A. Pitsillidis, G. Jordan, N. Weaver, C. Kreibich, B. Krebs, G. M. Voelker, S. Savage, and K. Levchenko. Pharmaleaks: Understanding the business of online pharmaceutical affiliate programs. In Proceedings of the 21st USENIX Security Symposium, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. M. Motoyama, K. Levchenko, C. Kanich, D. McCoy, G. M. Voelker, and S. Savage. Re: CAPTCHAS -- Understanding CAPTCHA--solving services in an economic context. In Proceedings of the 19th USENIX Security Symposium, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. M. Motoyama, D. McCoy, K. Levchenko, S. Savage, and G. M. Voelker. An analysis of underground forums. In Proceedings of ACM SIGCOMM Conference on Internet Measurement Conference (IMC), 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. A. Mukherjee, A. Kumar, B. Liu, J. Wang, M. Hsu, M. Castellanos, and R. Ghosh. Spotting opinion spammers using behavioral footprints. In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. M. Ott, C. Cardie, and J. Hancock. Estimating the prevalence of deception in online review communities. In Proceedings of the 21st International Conference on World Wide Web (WWW), 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Y. Park, J. Jones, D. McCoy, E. Shi, and M. Jakobsson. Scambaiter: Understanding targeted Nigerian scams on Craigslist. In Proceedings of the Network and Distributed System Security Symposium (NDSS), 2014.Google ScholarGoogle ScholarCross RefCross Ref
  33. G. Stringhini, G. Wang, M. Egele, C. Kruegel, G. Vigna, H. Zheng, and B. Zhao. Follow the green: Growth and dynamics in Twitter follower markets. In Proceedings of ACM SIGCOMM Conference on Internet Measurement Conference (IMC), 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. G. Swamynathan, K. C. Almeroth, and B. Y. Zhao. The design of a reliable reputation system. In Electronic Commerce Research, 10.3--4(2010):239--270. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. K. Thomas, C. Grier, V. Paxson, and D. Song. Suspended accounts in retrospect: An analysis of Twitter spam. In Proceedings of ACM SIGCOMM Conference on Internet Measurement Conference (IMC), 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. K. Thomas, D. McCoy, C. Grier, A. Kolcz, and V. Paxson. Trafficking fraudulent accounts: The role of the underground market in Twitter spam and abuse. In Proceedings of the 22nd USENIX Security Symposium, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. E-commerce Reputation Manipulation: The Emergence of Reputation-Escalation-as-a-Service

            Recommendations

            Comments

            Login options

            Check if you have access through your login credentials or your institution to get full access on this article.

            Sign in
            • Published in

              cover image ACM Other conferences
              WWW '15: Proceedings of the 24th International Conference on World Wide Web
              May 2015
              1460 pages
              ISBN:9781450334693

              Copyright © 2015 Copyright is held by the International World Wide Web Conference Committee (IW3C2)

              Publisher

              International World Wide Web Conferences Steering Committee

              Republic and Canton of Geneva, Switzerland

              Publication History

              • Published: 18 May 2015

              Permissions

              Request permissions about this article.

              Request Permissions

              Check for updates

              Qualifiers

              • research-article

              Acceptance Rates

              WWW '15 Paper Acceptance Rate131of929submissions,14%Overall Acceptance Rate1,899of8,196submissions,23%

            PDF Format

            View or Download as a PDF file.

            PDF

            eReader

            View online with eReader.

            eReader