  In 2020, Google announced it would disable third-party cookies in the Chrome
browser to improve user privacy. In order to continue to enable interest-based
advertising while mitigating risks of individualized user tracking, Google
proposed FLoC. The FLoC algorithm assigns users to "cohorts" that represent
groups of users with similar browsing behaviors so that ads can be served to
users based on their cohort. In 2022, after testing FLoC in a real world trial,
Google canceled the proposal with little explanation. In this work, we provide
a post-mortem analysis of two critical privacy risks for FloC by applying an
implementation of FLoC to a browsing dataset collected from over 90,000 U.S.
devices over a one year period. First, we show how, contrary to its privacy
goals, FLoC would have enabled cross-site user tracking by providing a unique
identifier for users available across sites, similar to the third-party cookies
FLoC was meant to be an improvement over. We show how FLoC cohort ID sequences
observed over time can provide this identifier to trackers, even with
third-party cookies disabled. We estimate the number of users in our dataset
that could be uniquely identified by FLoC IDs is more than 50% after 3 weeks
and more than 95% after 4 weeks. We also show how these risks increase when
cohort data are combined with browser fingerprinting, and how our results
underestimate the true risks FLoC would have posed in a real-world deployment.
Second, we examine the risk of FLoC leaking sensitive demographic information.
Although we find statistically significant differences in browsing behaviors
between demographic groups, we do not find that FLoC significantly risks
exposing race or income information about users in our dataset. Our
contributions provide insights and example analyses for future approaches that
seek to protect user privacy while monetizing the web.

Computers and Society