  Internet privacy is increasingly important on the modern Internet. Users are
looking to control the trail of data that they leave behind on the systems that
they interact with. Multi-Party Relay (MPR) architectures lower the traditional
barriers to adoption of privacy enhancing technologies on the Internet. MPRs
are unique from legacy architectures in that they are able to offer privacy
guarantees without paying significant performance penalties. Apple's iCloud
Private Relay is a recently deployed MPR service, creating the potential for
widespread consumer adoption of the architecture. However, many current
Internet-scale systems are designed based on assumptions that may no longer
hold for users of privacy enhancing systems like Private Relay. There are
inherent tensions between systems that rely on data about users -- estimated
location of a user based on their IP address, for example -- and the trend
towards a more private Internet.
  This work studies a core function that is widely used to control network and
application behavior, IP geolocation, in the context of iCloud Private Relay
usage. We study the location accuracy of popular IP geolocation services
compared against the published location dataset that Apple publicly releases to
explicitly aid in geolocating PR users. We characterize geolocation service
performance across a number of dimensions, including different countries, IP
version, infrastructure provider, and time. Our findings lead us to conclude
that existing approaches to IP geolocation (e.g., frequently updated databases)
perform inadequately for users of the MPR architecture. For example, we find
median location errors >1,000 miles in some countries for IPv4 addresses using
IP2Location. Our findings lead us to conclude that new, privacy-focused,
techniques for inferring user location may be required as privacy becomes a
default user expectation on the Internet.
