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 “bots and spiders or other crawlers masquerading as legitimate users.”
What are “bots and spiders or other crawlers masquerading as legitimate users” in the MRC definition of SIVT?
Bots and spiders or other crawlers represent non-human activity on the web. In some circumstances, these bots, spiders, or other crawlers are legitimate — e.g. “good” — but they are still non-human nonetheless. These “good” bots, spiders or crawlers are GIVT.
But there are “bad” bots, spiders, or crawlers that fall under the SIVT umbrella. Unlike known — e.g. “good” — crawlers, these crawlers may use standard browser identifiers.
If a crawler users standard browser identifiers, it means they are masquerading as a legitimate user. Web crawlers configured in this manner may occasionally serve a legitimate purpose such as testing page load times, but in many cases, the intent is to defraud and in both cases represent invalid impressions. Sophisticated analytics are employed to identify the signature of non-human crawlers operating in this manner.
MRC-accredited ad fraud detection and prevention companies must be able to identify and filter out bots, spiders, or other crawlers masquerading as legitimate users.
What are some other examples of SIVT?
Bots and spiders or other crawlers masquerading as legitimate users 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
- Hijacked devices, user sessions, ad tags, and ad creative
- Hidden/stacked/covered or otherwise intentionally obfuscated ad serving
- Invalid proxy traffic
- 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
