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CATCH: A detecting algorithm for coalition attacks of hit inflation in internet advertising
Authors:Chulyun Kim  Hui Miao  Kyuseok Shim
Affiliation:1. School of Electrical Engineering and Computer Science, Seoul National University, Kwanak, P.O. Box 34, Seoul 151-742, Republic of Korea;2. Department of Software Design and Management, Kyungwon University, Bokjeong-Dong, Sujeong-Gu, Seongnam, Gyeonggi-Do 461-701, Republic of Korea
Abstract:As the Internet flourishes, online advertising becomes essential for marketing campaigns for business applications. To perform a marketing campaign, advertisers provide their advertisements to Internet publishers and commissions are paid to the publishers of the advertisements based on the clicks made for the posted advertisements or the purchases of the products of which advertisements posted. Since the payment given to a publisher is proportional to the amount of clicks received for the advertisements posted by the publisher, dishonest publishers are motivated to inflate the number of clicks on the advertisements hosted on their web sites. Since the click frauds are critical for online advertising to be reliable, the online advertisers make the efforts to prevent them effectively. However, the methods used for click frauds are also becoming more complex and sophisticated.
Keywords:Click fraud  Hit inflation  Coalition attack  Internet advertising  Graph mining  Data mining
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