Understanding the Detection of View Fraud in Video Content Portals

TL;DR

This paper develops tools to evaluate the effectiveness of fraud detection systems in video portals, revealing strengths and vulnerabilities, especially in YouTube's system, and highlighting implications for advertisers.

Contribution

It introduces the first independent tools for auditing video view fraud detection systems and evaluates major platforms, uncovering performance differences and potential weaknesses.

Findings

YouTube's detection system outperforms others

YouTube's public and monetized view counters are inconsistently penalized

Fake views can still be monetized despite detection efforts

Abstract

While substantial effort has been devoted to understand fraudulent activity in traditional online advertising (search and banner), more recent forms such as video ads have received little attention. The understanding and identification of fraudulent activity (i.e., fake views) in video ads for advertisers, is complicated as they rely exclusively on the detection mechanisms deployed by video hosting portals. In this context, the development of independent tools able to monitor and audit the fidelity of these systems are missing today and needed by both industry and regulators. In this paper we present a first set of tools to serve this purpose. Using our tools, we evaluate the performance of the audit systems of five major online video portals. Our results reveal that YouTube's detection system significantly outperforms all the others. Despite this, a systematic evaluation indicates that it may still be susceptible to simple attacks. Furthermore, we find that YouTube penalizes its videos' public and monetized view counters differently, the former being more aggressive. This means that views identified as fake and discounted from the public view counter are still monetized. We speculate that even though YouTube's policy puts in lots of effort to compensate users after an attack is discovered, this practice places the burden of the risk on the advertisers, who pay to get their ads displayed.