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This paper presents an analytical system designed to detect click fraud on the Internet. The algorithm works with the data collected from an advertiser’s website to which the Pay-Per-Click traffic is directed. This traffic is not entirely carried out by humans, as a large part of it is carried out by bots – software running automated tasks. The purpose of the proposed algorithm is to analyze the data of individual clicks coming from advertisements and to automatically classify them as suspicious or correct. The paper presents the mechanisms of comparing different types of data, their classification and the tuning of particular elements of the algorithm. Results of the experimental research confirming the effectiveness of the proposed methods are also presented.