A Connected Vehicle
Network is designed to provide a secure and private method for drivers to use
the roads in a certain area most efficiently. Cars connect to access points
(Wi-Fi, 3G, LTE) through a central authority like a cloud. The cloud monitors
and analyzes the car’s movements and other functions in order to provide
certain services to the driver, like driving instructions.
However, the cloud also
provides a service called usage-based insurance (UBI). Usage-based insurance is
automobile insurance in which the insurer uses data on driving behavior to set
the premium offered to each policyholder. The premiums are adjusted to reflect
the individual driver risk profiles based on their driving habits. In order to
calculate the risk of each driver properly, the insurance company has to know
several driving attributes including total driving time, cornering, and average
speed. Commercial UBI programs available today are mainly based on information
extracted from the car’s on-board-diagnostics (OBD) system, or from externally
installed hardware components, referred to as black-boxes or aftermarket
devices.
Recently, BGU researchers have shown that it is possible, in many
cases, to reconstruct a driver’s route from various driving attributes provided
to UBI companies, such as cornering events, average speed and total driving
time even in cases where the GPS did not track the full route. This breach of
privacy could be used to discover a driver’s whereabouts, home, work, who they
meet with and many other types of information that a hostile organization could
exploit.
The research was
conducted by Prof. Michael Segal from the Department of Communication Systems Engineering and his
Master’s student, Mr. Vladimir Kaplun. The research was part of Kaplun’s thesis
and will be submitted to conferences and journals in the future. The research
was supported by the IBM CyberSecurity Center of Excellence at BGU.
Prof. Segal is a past head of the Department and
also held a visiting professorship at Cambridge University. Prof. Segal serves
as the Managing Editor of one of the most influential journals in the area of
computer and system sciences, the Journal of Computer and System Sciences.
