  We consider traffic-update mobile applications that let users learn traffic
conditions based on reports from other users. These applications are becoming
increasingly popular (e.g., Waze reported 30 million users in 2013) since they
aggregate real-time road traffic updates from actual users traveling on the
roads. However, the providers of these mobile services have access to such
sensitive information as timestamped locations and movements of its users. In
this paper, we describe Haze, a protocol for traffic-update applications that
supports the creation of traffic statistics from user reports while protecting
the privacy of the users. Haze relies on a small subset of users to jointly
aggregate encrypted speed and alert data and report the result to the service
provider. We use jury-voting protocols based on threshold cryptosystem and
differential privacy techniques to hide user data from anyone participating in
the protocol while allowing only aggregate information to be extracted and sent
to the service provider. We show that Haze is effective in practice by
developing a prototype implementation and performing experiments on a
real-world dataset of car trajectories.
