On the security of pay-per-click and other Web advertising schemes
WWW '99 Proceedings of the eighth international conference on World Wide Web
Combating click fraud via premium clicks
SS'07 Proceedings of 16th USENIX Security Symposium on USENIX Security Symposium
Click fraud resistant methods for learning click-through rates
WINE'05 Proceedings of the First international conference on Internet and Network Economics
MobiAd: private and scalable mobile advertising
Proceedings of the fifth ACM international workshop on Mobility in the evolving internet architecture
Privad: practical privacy in online advertising
Proceedings of the 8th USENIX conference on Networked systems design and implementation
Understanding fraudulent activities in online ad exchanges
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Measuring and fingerprinting click-spam in ad networks
Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication
Measuring and fingerprinting click-spam in ad networks
ACM SIGCOMM Computer Communication Review - Special october issue SIGCOMM '12
Duplicate detection in pay-per-click streams using temporal stateful Bloom filters
International Journal of Data Analysis Techniques and Strategies
Dissecting ghost clicks: ad fraud via misdirected human clicks
Proceedings of the 28th Annual Computer Security Applications Conference
Verifiable auctions for online ad exchanges
Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM
ViceROI: catching click-spam in search ad networks
Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security
Challenges of keyword-based location disclosure
Proceedings of the 12th ACM workshop on Workshop on privacy in the electronic society
Impression fraud in online advertising via pay-per-view networks
SEC'13 Proceedings of the 22nd USENIX conference on Security
DECAF: detecting and characterizing ad fraud in mobile apps
NSDI'14 Proceedings of the 11th USENIX Conference on Networked Systems Design and Implementation
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Online advertising is currently the richest source of revenue for many Internet giants. The increased number of online businesses, specialized websites and modern profiling techniques have all contributed to an explosion of the income of ad brokers from online advertising. The single biggest threat to this growth, is however, click-fraud. Trained botnets and individuals are hired by click-fraud specialists in order to maximize the revenue of certain users from the ads they publish on their websites, or to launch an attack between competing businesses. In this note we wish to raise the awareness of the networking research community on potential research areas within the online advertising field. As an example strategy, we present Bluff ads; a class of ads that join forces in order to increase the effort level for click-fraud spammers. Bluff ads are either targeted ads, with irrelevant display text, or highly relevant display text, with irrelevant targeting information. They act as a litmus test for the legitimacy of the individual clicking on the ads. Together with standard threshold-based methods, fake ads help to decrease click-fraud levels.