A Proposal to Prevent Click-Fraud Using Clickable CAPTCHAs

Advertising on the Internet is a key factor for the success of several businesses nowadays. The Internet has evolved to a point where it has become possible to develop a business model completely based on Web advertising, which is important for the consolidation of such a model and the continuity of the Internet itself. However, it is often observed that some content publishers are dishonest and employ automated tools to generate traffic and profit by defrauding advertisers. Similarly, some advertisers use automated tools to click on the ads of their competitors, aiming to exhaust the budget of the competitor's marketing departments. In this paper, differently of recent click fraud detection mechanisms, that take place after the fraud has already occurred, we propose an approach for preventing automated click-fraud, based on the use of click able CAPTCHAs.

[1]  Divyakant Agrawal,et al.  Duplicate detection in click streams , 2005, WWW '05.

[2]  Hamed Haddadi,et al.  Fighting online click-fraud using bluff ads , 2010, CCRV.

[3]  Jon Howell,et al.  Asirra: a CAPTCHA that exploits interest-aligned manual image categorization , 2007, CCS '07.

[4]  Patrice Y. Simard,et al.  Best practices for convolutional neural networks applied to visual document analysis , 2003, Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings..

[5]  John Langford,et al.  CAPTCHA: Using Hard AI Problems for Security , 2003, EUROCRYPT.

[6]  Jitendra Malik,et al.  Recognizing objects in adversarial clutter: breaking a visual CAPTCHA , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[7]  Stelvio Cimato,et al.  SAWM: a tool for secure and authenticated web metering , 2002, SEKE '02.

[8]  Markus Jakobsson,et al.  Combating Click Fraud via Premium Clicks , 2007, USENIX Security Symposium.

[9]  A. M. Turing,et al.  Computing Machinery and Intelligence , 1950, The Philosophy of Artificial Intelligence.

[10]  Benny Pinkas,et al.  On the Security of Pay-per-Click and Other Web Advertising Schemes , 1999, Comput. Networks.

[11]  Daniel V. Klein Defending Against the Wily Surfer-Web-based Attacks and Defenses , 1999, Workshop on Intrusion Detection and Network Monitoring.

[12]  Divyakant Agrawal,et al.  Detectives: detecting coalition hit inflation attacks in advertising networks streams , 2007, WWW '07.