Mobile ads are plagued with fraudulent clicks which is a major challenge for the advertising community. Although popular ad networks use many techniques to detect click fraud, they do not protect the client from possible collusion between publishers and ad networks. In addition, ad networks are not able to monitor the user’s activity for click fraud detection once they are redirected to the advertising site after clicking the ad. We propose a new crowdsource-based system called Click Fraud Crowdsourcing (CFC) that collaborates with both advertisers and ad networks in order to protect both parties from any possible click fraudulent acts. The system benefits from both a global view, where it gathers multiple ad requests corresponding to different ad network-publisher-advertiser combinations, and a local view, where it is able to track the users’ engagement in each advertising website. The results demonstrated that our approach offers a lower false positive rate (0.1) when detecting click fraud as opposed to proposed solutions in the literature, while maintaining a high true positive rate (0.9). Furthermore, we propose a new mobile ad charging model that benefits from our system to charge advertisers based on the duration spent in the advertiser’s website.

中文翻译：

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用于点击欺诈检测的众包

移动广告经常遭受欺诈性点击的困扰，这是广告界面临的主要挑战。尽管流行的广告网络使用许多技术来检测点击欺诈，但是它们并不能保护客户端免受发布者与广告网络之间可能的串通。另外，一旦广告网络在点击广告后被重定向到广告网站，就无法监视用户的点击欺诈检测活动。我们提出了一种新的基于众包的系统，称为点击欺诈众包（CFC），该系统可与广告商和广告网络合作，以保护双方免受任何可能的点击欺诈行为的侵害。该系统受益于全局视图（在本地视图中收集对应于不同广告网络-发布者-广告商组合的多个广告请求）和本地视图，可以跟踪用户在每个广告网站中的参与度。结果表明，与文献中提出的解决方案相比，我们的方法在检测点击欺诈时提供了较低的误报率（0.1），同时保持了较高的真实率（0.9）。此外，我们提出了一种新的移动广告收费模型，该模型可从我们的系统中受益，该模型根据广告客户网站上花费的时间为广告客户收费。