Tagging Click-Spamming Suspicious Installs in Mobile Advertising Through Time Delta Distributions

Abstract

Fraud in the mobile advertising world is a topic gaining momentum recently. Different reports agree that invalid traffc is generating losses in the order of billions of dollars and that there is a signi cant amount of fraud with ongoing efforts against it. Here at Jampp1 we use an automated fraud detection algorithm for a recent type of mobile advertising fraud, which can be referred to as click-spamming, click-injection or mobile-hijacking. We propose a metric to measure suspicious installs, and use a heuristic to compare the ts of theoretical distributions to this metric. This allows us to derive a threshold for suspicious installs. Our metric is based on the time-delta distributions, which amounts to the time it takes from a click in an ad to be converted into an install. The model is currently in use with satisfactory results. To the best of our knowledge, this is the rst algorithm in production used to tackle this speci c kind of fraud.