Secure multi-party computation (MPC) allows multiple parties
to jointly compute the output of a function while preserving
the privacy of any individual party’s inputs to that function.
As MPC protocols transition from research prototypes to realworld
applications, the usability of MPC-enabled applications
is increasingly critical to their successful deployment and
widespread adoption. Our Web-MPC platform, designed with
a focus on usability, has been deployed for privacy-preserving
data aggregation initiatives with the City of Boston and the
Greater Boston Chamber of Commerce. After building and
deploying an initial version of the platform, we conducted a
heuristic evaluation to identify usability improvements and
implemented corresponding application enhancements. However,
it is difficult to gauge the effectiveness of these changes
within the context of real-world deployments using traditional
web analytics tools without compromising the security guarantees
of the platform. This work consists of two contributions
that address this challenge: (1) the Web-MPC platform has
been extended with the capability to collect web analytics
using existing MPC protocols, and (2) as a test of this feature
and a way to inform future work, this capability has been
leveraged to conduct a usability study comparing the two versions
ofWeb-MPC. While many efforts have focused on ways
to enhance the usability of privacy-preserving technologies,
this study serves as a model for using a privacy-preserving
data-driven approach to evaluate and enhance the usability of
privacy-preserving websites and applications deployed in realworld
scenarios. Data collected in this study yields insights
into the relationship between usability and security; these can
help inform future implementations of MPC solutions.Published versio