Biblio

Traditionally, the vehicle has been the extension of the manual ambulatory system, docile to the drivers' commands. Recent advances in communications, controls and embedded systems have changed this model, paving the way to the Intelligent Vehicle Grid. The car is now a formidable sensor platform, absorbing information from the environment, from other cars (and from the driver) and feeding it to other cars and infrastructure to assist in safe navigation, pollution control and traffic management. The next step in this evolution is just around the corner: the Internet of Autonomous Vehicles. Like other important instantiations of the Internet of Things (e.g., the smart building, etc), the Internet of Vehicles will not only upload data to the Internet with V2I. It will also use V2V communications, storage, intelligence, and learning capabilities to anticipate the customers' intentions and learn from other peers. V2I and V2V are essential to the autonomous vehicle, but carry the risk of attacks. This paper will address the privacy attacks to which vehicles are exposed when they upload private data to Internet Servers. It will also outline efficient methods to preserve privacy.

Today, mobile data owners lack consent and control over the release and utilization of their location data. Third party applications continuously process and access location data without data owners granular control and without knowledge of how location data is being used. The proliferation of GPS enabled IoT devices will lead to larger scale abuses of trust. In this paper we present the first design and implementation of a privacy module built into the GPSD daemon. The GPSD daemon is a low-level GPS interface that runs on GPS enabled devices. The integration of the privacy module ensures that data owners have granular control over the release of their GPS location. We describe the design of our privacy module integration into the GPSD daemon.