Pixalate is an MRC-accredited company for the detection and filtration of Sophisticated Invalid Traffic ("SIVT") desktop and mobile web impressions.
According to the Media Rating Council’s (MRC) standards for Invalid Traffic Detection and Filtration Guidelines, there are two types of invalid traffic:
One example of SIVT is “invalid proxy traffic.”
What is “invalid proxy traffic” in the MRC definition of SIVT?
According to the MRC, invalid proxy traffic is considered SIVT. But what is it?
For starters, note that there are legitimate uses for web proxies — such as servers acting as corporate internet gateways.
However, many proxies frequently hide or facilitate fraudulent activity.
Per the MRC, invalid proxy traffic can originate “from an intermediary proxy device that exists to manipulate traffic counts or create/pass-on non-human or invalid traffic or otherwise failing to meet protocol validation.”
For example, such invalid proxies may be used to route bot traffic originating from data centers in order to make its origins appear to be an ordinary home or business. Characteristics of such traffic are, in fact, distinguishable from valid proxy traffic using advanced analytics.
MRC-accredited ad fraud detection and prevention companies must be able to identify and filter invalid proxy traffic.
What are some other examples of SIVT?
Invalid proxy traffic is just one example of Sophisticated Invalid Traffic (SIVT) as defined by the MRC. To learn about some of the other examples of SIVT, click on any of the examples below:
- Differentiating human and IVT traffic when originating from the same or similar source
- Bots and spiders or other crawlers masquerading as legitimate users
- Hijacked devices, user sessions, ad tags, and ad creative
- Hidden/stacked/covered or otherwise intentionally obfuscated ad serving
- Adware and malware
- Incentivized manipulation of measurements
- Falsified viewable impression decisions
- Falsely represented sites
- Cookie stuffing, recycling, or harvesting
- Manipulation or falsification of location data