An effective method for combating malicious scripts clickbots

Abstract

Online advertising has been suffering serious click fraud problem. Fraudulent publishers can generate false clicks using malicious scripts embedded in their web pages. Even widely-used security techniques like iframe cannot prevent such attack. In this paper, we propose a framework and associated methodologies to automatically and quickly detect and filter false clicks generated by malicious scripts. We propose to create an impression-click identifier which is able to link corresponding impressions and clicks together with a predefined lifetime. The impression-click identifiers are stored in a special data structure and can be later validated upon a click is received. The framework has the nice features of constant-time inserting and querying, low false positive rate and low quantifiable false negative rate. From our experimental evaluation on a primitive PC machine, our approach can achieve a false negative rate 0.00008 using 120MB memory and average inserting and querying time is 3 and 1 microseconds, respectively. © 2009 Springer Berlin Heidelberg.