Ad Fraud is a broad term that covers any instance of scammers stealing money from digital advertisers by tricking the systems that connect advertisers with customers, and getting paid for doing something that they’re really not doing. In other words, it’s anything that purposely prevents ads from getting served to the right people at the right time in the right place, in order to profit from that mis-use.

Taking Advantage of the System by Jefferson Santos on Unsplash

Before digital advertising became the dominant form of advertising, the process of buying ads was much simpler. Advertisers would work directly with the publishers they wanted to run ads through, and publishers would provide exact statistics on when and where that ad ran. Sure, there was always the risk that a newspaper might overstate their total number of subscriptions, but advertisers could at least pick up a copy of the paper and see that their ad was running where it was supposed to be. There just weren’t many opportunities for fraud.

As digital advertising took over, and the process of buying and distributing digital advertising became more complicated, more opportunities for fraud emerged, and unscrupulous scammers would insert themselves into the process to skim off some of the advertiser’s budget.

Making Money by Marco Xu on Unsplash

While you might imagine that ad fraud is just a few extra clicks here and there, it’s actually a HUGE issue. Forrester determined that as much as 56% of all display ad dollars were lost to fraudulent or un-viewable inventory, which means upwards of $7.4 billion is wasted every year, and that’s money that could be going towards reaching legitimate customers. As budgets continue to rise, and the way that digital advertising is purchased continues to get more complicated, fraudsters are finding new ways to steal even more money from advertisers.

As we design and develop Varanida, one of the benefits of creating an advertising ecosystem that runs on the blockchain is that it eliminates many of the opportunities for ad fraud that currently exist. Since these methods of ad fraud can be hard to understand, we thought it would be helpful to offer an overview of some of the most common forms of ad fraud we’re working to eliminate:

• Domain Fraud: Sites and apps pose as legitimate publishers, either by generating an illegitimate website from scratch, or by plagiarizing content from actual publishers. Also called Domain Spoofing, this is common on Real-Time Bidding systems, where sometimes publishers are allowed to declare their own domain and site ID, without being verified. For example, an advertiser might want to reach sports fans on ESPN.com, but their ads are actually appearing on a site that has just copied the appearance and content of ESPN, and is being viewed by illegitimate traffic that is just there to interact with the ads and generate advertising revenue for the site owner.

• Traffic Fraud: One of the most common forms of ad fraud, this is where sites and apps boost their impressions, clicks, or other website activity counts to increase the revenue they generate from their advertising. This can be done with bots that create machine-generated impressions or other actions designed to mimic actual human patterns, or through low-wage workers who are paid to interact with sites or apps to generate valueless clicks, since they have no intention of engaging with the advertiser beyond that initial click. This category also includes Retargeting Fraud, where scammers will mimic the human interaction that signals interest in a particular brand, such as visiting that brand’s website, in order to take advantage of the retargeting ads that typically pay a higher amount since that audience is perceived as being more valuable. Even name-brand publishers can get caught up in the mix, as they too will sometimes buy traffic to boost their pageviews, and the sellers of that traffic aren’t always truthful about where it comes from.

• Location Fraud: Advertisers are willing to pay more money to reach certain geographic areas, so an ad that shows in San Francisco, CA might cost the advertiser 10X what that same ad would cost to show a person in Hong Kong. With location fraud, app developers, ad networks, or ad exchanges falsify the location of their users to drive up the cost of advertising, so even though the ad is reaching a real person, the advertiser is paying more than they should to reach that person, and they’re often reaching people in areas that they aren’t trying to target. This is especially common for mobile inventory, where advertisers are relying on the ad network or exchange to correctly report where their traffic is originating from.

• Attribution Fraud: Another common form of ad fraud happens when a scammer will trick an ad network into giving them credit for something they didn’t actually do. One of the most common forms of attribution fraud is Cookie Stuffing, where a third-party site will add its cookie to a user’s browser (often by loading that site into an invisible, 1x1 pixel iFrame) making it look like that user visited the third-party site and interacted with advertising on that page. Then, for example, if the user buys something from a site that pays affiliates for driving a sale, they get credit for creating that sale, instead of the site that the user actually saw the ad on.

• Viewability Fraud: This covers a variety of tricks that scammers use to serve ads in ways that aren’t viewable by actual visitors, but they still get paid for serving that ad. For example, Ad Stacking is where a scammer will stack a number of different ads on top of one another in a single ad placement, so they get paid for each impression, even though a real person only sees the top ad. Another example is Pixel Stuffing, where a scammer will serve ads in an invisible 1x1 pixel iFrame, or even load up a whole page filled with ads inside of that iFrame. This is often used with auto-play videos that start without audio, to take advantage fo the higher revenue generated by the more valuable video ad impression.

As you can see, scammers use a wide variety of tactics to try and take advantage of the current advertising system, and steal money from advertisers. At Varanida, our goal is to offer an advertising network where data integrity is ensured for both publishers and advertisers, and we’re doing that with a mix of machine-learning algorithms and in-house development.

Machine Learning by Luca Bravo on Unsplash

To help combat ad fraud, all clicks and impressions are analyzed by the Varanida Network. Invalid requests or invalid traffic will be filtered out, but will still be visible to all parties, making reporting and performance monitoring not only transparent, but also trustworthy.

In addition, each advertiser, publisher, and user is given a unique ID, and their history can be audited through a public ledger. This history will be used to create a reputation rank, called VADkarma. Depending on the quality of their interaction with the Varanida Network, the reputation rank may increase or decrease, and this rank can be used to help filter out fraudulent activity.

Fighting fraud is a never-ending battle, since there are always going to be people that look for ways to take advantage of the system. (Currently a lot of fraud actually comes from ad buying middlemen that are incentivized to make the stats lie, or they get commissions for choosing one ad network over another, but that’s another story…)

Our hope is that by leveraging the benefits of the blockchain, and by designing a fraud-proof platform from the very beginning, Varanida will be one place where advertisers can feel confident that they’re reaching real people with their advertising budgets, and not just putting money in the pockets of scammers and fraudsters.