DETECTING COALITION FRAUD IN ONLINE ADVERTISING

摘要

The present teaching, which includes methods, systems and computer-readable media, relates to detecting online coalition fraud. The disclosed techniques may include grouping visitors that interact with online content into clusters, obtaining traffic features for each visitor, wherein the traffic features are based at least on data representing the corresponding visitor's interaction with the online content; determining, for each cluster, cluster metrics based on (one or more statistical values of) the traffic features of the visitors in that cluster; and determining whether a cluster is fraudulent based on the cluster metrics of the first cluster. For example, determining whether a cluster is fraudulent may include determining whether a first statistical value of the traffic features related to the first cluster is greater than a first threshold value, and/or determining whether a second statistical value of the traffic features related to the first cluster is lower than a second threshold value.