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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.