Privacy Pass for digital ads verification

• Upcoming
• Tentative
• Breakout Sessions

Device spoofing is a pervasive problem in digital ads, with bots masquerading as user devices, and bad actors spoofing high-value Connected TV inventory. This results in wasted ad spend for advertisers and reduced ad revenue for legitimate publishers. The Privacy Pass protocol, which enables devices to assert their authenticity in a privacy-preserving manner, has been adopted for a digital ads verification use case. This implementation is being standardized within the IAB Tech Lab's Open Measurement SDK to simplify broad adoption by publishers. Using this mechanism, Verifiers (Origins in Privacy Pass), which are typically Traffic Quality / ad verification vendors, will be able to uncover sellers of spoofed inventory and take enforcement actions on them.

We will present the mechanism and how a "positive" and anonymous signal that does not have 100% coverage can be used for fraud detection.

Agenda

Chairs:
Vinod Panicker

Description:
Device spoofing is a pervasive problem in digital ads, with bots masquerading as user devices, and bad actors spoofing high-value Connected TV inventory. This results in wasted ad spend for advertisers and reduced ad revenue for legitimate publishers. The Privacy Pass protocol, which enables devices to assert their authenticity in a privacy-preserving manner, has been adopted for a digital ads verification use case. This implementation is being standardized within the IAB Tech Lab's Open Measurement SDK to simplify broad adoption by publishers. Using this mechanism, Verifiers (Origins in Privacy Pass), which are typically Traffic Quality / ad verification vendors, will be able to uncover sellers of spoofed inventory and take enforcement actions on them.

We will present the mechanism and how a "positive" and anonymous signal that does not have 100% coverage can be used for fraud detection.

Goal(s):
To create awareness of a new fraud detection use case implemented with Privacy Pass and to solicit feedback on potential improvements.

Materials:

• Session proposal on GitHub

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