Impression Fraud in Online Advertising via Pay-Per-View ... - CiteSeerX

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Impression Fraud in Online Advertising via Pay-Per-View Networks Kevin Springborn

Paul Barford

Broadcast Interactive Media

Broadcast Interactive Media University of Wisconsin-Madison

[email protected]

[email protected] ABSTRACT

The online ad ecosystem can roughly be divided into three groups: advertisers, publishers and intermediaries. Advertisers pay publishers to place a specified volume of creative content with embedded links (i.e., text, display or video ads) on websites and apps. Intermediaries (e.g., ad servers and ad exchanges) are often used to facilitate connections between publishers and advertisers. Intermediaries typically place a surcharge on the fees paid by advertisers to publishers for ad placements and/or ad clicks. What is immediately obvious from this simple description is that publisher and intermediary platform revenues are directly tied to the number of daily visits to a website or app. Thus, there are strong incentives for publishers and intermediaries to use any means available to drive user traffic to publisher sites. There are certainly legitimate methods for traffic generation for publisher sites. The most widely used are the text-based ad words that appear in search results e.g., from Google or Bing. However, it can be quite difficult and expensive to drive large traffic volumes to target sites using ad words alone.1 Thus, other methods for traffic generation have emerged, many of which are deeded as fraudulent by advertisers and intermediaries. Google defines invalid (fraudulent) traffic as follows:2

Advertising is one of the primary means for revenue generation for millions of websites and mobile apps. While the majority of online advertising revenues are based on payper-click, alternative forms such as impression-based display and video advertising have been growing rapidly over the past several years. In this paper, we investigate the problem of invalid traffic generation that aims to inflate advertising impressions on websites. Our study begins with an analysis of purchased traffic for a set of honeypot websites. scrolling=’auto’> ...

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