Fighting online click-fraud using bluff ads

Author:

Haddadi Hamed1

Affiliation:

1. University of London, London, United Kingdom

Abstract

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.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Software

Reference6 articles.

1. On the security of pay-per-click and other Web advertising schemes

2. Click Fraud Resistant Methods for Learning Click-Through Rates

3. C. Labovitz S. Iekel-Johnson D. McPherson F. J. J. Oberheide and M. Karir. ATLAS Internet Observatory 2009 Annual Report. NANOG47 http://tinyurl.com/yz7xwvv June 2009. C. Labovitz S. Iekel-Johnson D. McPherson F. J. J. Oberheide and M. Karir. ATLAS Internet Observatory 2009 Annual Report. NANOG47 http://tinyurl.com/yz7xwvv June 2009.

4. J. Stewart. FFSearcher Click Fraud Tro jan. http://secureworks.com/research/threats/ffsearcher/ June 2009. J. Stewart. FFSearcher Click Fraud Tro jan. http://secureworks.com/research/threats/ffsearcher/ June 2009.

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