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Revealing, characterizing, and detecting crowdsourcing spammers: A case study in community QA

机译:揭示,表征和检测众包垃圾邮件发送者:社区问答中的案例研究

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Crowdsourcing services have emerged and become popular on the Internet in recent years. However, evidence shows that crowdsourcing can be maliciously manipulated. In this paper, we focus on the “dark side” of the crowdsourcing services. More specifically, we investigate the spam campaigns that are originated and orchestrated on a large Chinese-based crowdsourcing website, namely ZhuBaJie.com, and track the crowd workers to their spamming behaviors on Baidu Zhidao, the largest community-based question answering (QA) site in China. By linking the spam campaigns, workers, spammer accounts, and spamming behaviors together, we are able to reveal the entire ecosystem that underlies the crowdsourcing spam attacks. We present a comprehensive and insightful analysis of the ecosystem from multiple perspectives, including the scale and scope of the spam attacks, Sybil accounts and colluding strategy employed by the spammers, workers' efforts and monetary rewards, and quality control performed by the spam campaigners, etc. We also analyze the behavioral discrepancies between the spammer accounts and the legitimate users in community QA, and present methodologies for detecting the spammers based on our understandings on the crowdsourcing spam ecosystem.
机译:近年来,众包服务已经出现并在Internet上变得流行。但是,有证据表明,众包可以被恶意操纵。在本文中,我们重点关注众包服务的“阴暗面”。更具体地说,我们调查了一个大型的基于中国的众包网站(ZhuBaJie.com)上发起和策划的垃圾邮件活动,并在最大的基于社区的问题解答(QA)百度之道上跟踪人群工作者的垃圾邮件行为。中国的网站。通过将垃圾邮件活动,工作人员,垃圾邮件发送者帐户和垃圾邮件行为链接在一起,我们能够揭示构成众包垃圾邮件攻击基础的整个生态系统。我们从多个角度对生态系统进行了全面而深入的分析,包括垃圾邮件攻击的规模和范围,垃圾邮件发送者使用的Sybil帐户和串谋策略,工人的努力和金钱奖励以及垃圾邮件活动者执行的质量控制,我们还分析了垃圾邮件发送者帐户与社区质量检查中合法用户之间的行为差​​异,并根据我们对众包垃圾邮件生态系统的理解,提出了检测垃圾邮件发送者的方法。

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