HUMAN measures a variety of signals to determine whether traffic is valid or invalid. Based on these signals, invalid traffic (also known as IVT) is further categorized as General IVT or Sophisticated IVT. In some cases, HUMAN will return additional information about the specific signals that drove our decisioning.
These examples are meant to illustrate some of the differences between IVT types. However, this is only a subset of all possible invalid behaviors and tactics and is not a complete list.
General IVT (GIVT)
Ad traffic originating from servers in data centers whose IPs are linked to invalid activity (such as non-human traffic). This traffic usually originates from known data center IPs that are included in an industry list, such as the Trustworthy Accountability Group (TAG) Data Center IP List.
Example: TAG Data Center IP List
A program or automated script that requests web content, but is not malicious and declares itself as non-human through a variety of standard identification mechanisms. These crawlers are usually included in the IAB International Spiders and Bots List.
Example: IAB Spiders and Bots List
Ad traffic that exhibits one or more attributes (e.g., user cookies) associated with known irregular patterns, such as auto-refresh traffic or duplicate clicks.
Example: False representation
Sophisticated IVT (SIVT)
A program or automated script that requests web content (including digital ads) without user involvement and without declaring itself as a crawler. These programs and scripts are often used for malicious purposes.
An ad request for inventory that is different from the actual inventory being supplied, including ad requests where the actual ad is rendered to a different website or application, device, or other target (such as geography).
Examples: Spoofed measurement, domain spoofing, emulators masquerading
Misleading user interface
A web page, application, or other visual element that has been modified to falsely include one or more ads in an unintended location. This includes ads that are rendered without being visible or ads that may trick users into unintentionally clicking on them.
Examples: Stacked ads, hidden ads
A browser, application, or other program that triggers ad interactions without a user’s consent, such as an unintended click, an unexpected conversion, or false attribution for mobile app installations.
Examples: Pop-unders, aggressive pop-ups, forced new window
Invalid traffic that cannot be classified using any of the other categories listed here, or invalid traffic discovered using sensitive techniques that HUMAN cannot disclose.
Examples: Machine learning models, sensitive invalid traffic