  Intelligent infrastructure will critically rely on the dense instrumentation
of sensors and actuators that constantly transmit streaming data to cloud-based
analytics for real-time monitoring. For example, driverless cars communicate
real-time location and other data to companies like Google, which aggregate
regional data in order to provide real-time traffic maps. Such traffic maps can
be extremely useful to the driver (for optimal travel routing), as well as to
city transportation administrators for real-time accident response that can
have an impact on traffic capacity. Intelligent infrastructure monitoring
compromises the privacy of drivers who continuously share their location to
cloud aggregators, with unpredictable consequences.
  Without a framework for protecting the privacy of the driver's data, drivers
may be very conservative about sharing their data with cloud-based analytics
that will be responsible for adding the intelligence to intelligent
infrastructure. In the energy sector, the Smart Grid revolution relies
critically on real-time metering of energy supply and demand with very high
granularity. This is turn enables real-time demand response and creates a new
energy market that can incorporate unpredictable renewable energy sources while
ensuring grid stability and reliability. However, real-time streaming data
captured by smart meters contain a lot of private information, such as our home
activities or lack of, which can be easily inferred by anyone that has access
to the smart meter data, resulting not only in loss of privacy but potentially
also putting us at risk.
