Abstract: Methods and systems for fraudulent traffic detection and estimation are disclosed. Initially, an empirical distribution of a plurality of features based on a first plurality of datapoints for the plurality of features is received. Next, a model distribution of the plurality of features based on a second plurality of datapoints for the plurality of features is received. Then, it is determined, a minimum number of datapoints to remove from the first plurality of datapoints to create a modified empirical distribution corresponding to the model distribution within a first significance level. Finally, an alert that the first plurality of web traffic includes at least one fraudulent instance of web traffic is generated in response to the determination that the minimum number of datapoints is greater than a first threshold.

Abstract: Methods and systems for fraudulent traffic detection and estimation are disclosed. Initially, an empirical distribution of a plurality of features based on a first plurality of datapoints for the plurality of features is received. Next, a model distribution of the plurality of features based on a second plurality of datapoints for the plurality of features is received. Then, it is determined, a minimum number of datapoints to remove from the first plurality of datapoints to create a modified empirical distribution corresponding to the model distribution within a first significance level. Finally, an alert that the first plurality of web traffic includes at least one fraudulent instance of web traffic is generated in response to the determination that the minimum number of datapoints is greater than a first threshold.