In this talk, we will describe VPriv, a system that can be used by
several such applications without violating the locational privacy of drivers.
The starting point is the observation that in many applications, some
centralized server needs to compute a function of a car's or user's path --- a
list of time-position tuples. VPriv provides two components:
1) an efficient protocol and implementation to compute path functions in a way
that does not reveal anything more than the result of the function to the
server, and
2) an out-of-band enforcement mechanism using random spot checks that allows
the server and application to handle misbehaving cars or users.

Our implementation of VPriv is efficient enough to be run on inexpensive stock
devices. Using analysis and simulation based on real vehicular data collected
over two months from the CarTel project testbed of 27 taxis running in an urban
area, we demonstrate that our protocol is resistant to a range of possible
attacks.

This is joint work with Professor Hari Balakrishnan and Andrew J. Blumberg, Ph.D.

Web page http://www.mit.edu/~ralucap/