Big Bird: Resilient Privacy Budgeting Across Untrusted Web Domains
cs.CR
Submitted: 2025-06-05
Updated: 2026-09-13
Comments: v2: generalized per-querier soundness results and restructured paper; v3: improved evaluation and threat model; v4: SOSP '26 camera-ready
Journal ref: SOSP '26: Proceedings of the ACM SIGOPS 32nd Symposium on Operating Systems Principles. September 29th - October 2nd, 2026. Prague, Czech Republic
Code: https://github.com/columbia/pdslib
Project page: https://w3c.github.io/attribution
License: http://creativecommons.org/licenses/by-sa/4.0/
The gist: The W3C Attribution API is an emerging standard for privacy-preserving advertising measurement.
Terminology
Abstract
The W3C Attribution API is an emerging standard for privacy-preserving advertising measurement. Its current privacy architecture enforces individual differential privacy (IDP) independently for each domain (e.g., an advertiser) issuing queries. We show that this guarantee is unsound under realistic system behavior: it fails under cross-querier data adaptivity and can also fail when shared limits are enforced across queriers. The issue is not the on-device accounting model itself -- device-epoch IDP -- but treating each querying domain in isolation. We propose Big Bird, a privacy-budget manager that makes global device-epoch IDP -- enforced jointly across all domains -- both sound and deployable for Attribution. Big Bird addresses the main obstacle to global enforcement in open multi-querier systems: denial-of-service depletion of a shared global budget by Sybil web domains. Its key insight is that benign Attribution workloads have a stock-and-flow structure: impressions create potential privacy loss, conversions realize it, and meaningful budget consumption should be tied to genuine user actions across distinct web domains. Big Bird enforces this structure with privacy-loss-based quotas on impression and conversion sites and a per-user-action cap on how many quotas can be activated, ensuring that adversarial impact scales with genuine user interactions rather than with the number of Sybil domains. We implement Big Bird in Rust, integrate it into Firefox's Attribution prototype, and evaluate it theoretically and empirically on real ad-tech data. We show that Big Bird provides rigorous global device-epoch IDP, formal resilience to depletion attacks, and utility for benign queriers under attack.
Sources
- PSI ({\Psi}): a Private data Sharing Interface
- Practical Privacy Filters and Odometers with R'enyi Differential Privacy and Applications to Differentially Private Deep Learning
- CriteoPrivateAds: A Real-World Bidding Dataset to Design Private Advertising Systems
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