Automobile Driver Fingerprinting

Abstract: Today’s automobiles leverage powerful sensors and embedded computers to optimize efficiency, safety, and driver engagement. However the complexity of possible inferences using in-car sensor data is not well understood. While we do not know of attempts by automotive manufacturers or makers of after-market components (like insurance dongles) to violate privacy, a key question we ask is: could they (or their collection and later accidental leaks of data) violate a driver’s privacy? In the present study, we experimentally investigate the potential to identify individuals using sensor data snippets of their natural driving behavior. More specifically we record the in-vehicle sensor data on the controllerarea-network (CAN) of a typical modern vehicle (popular 2009 sedan) as each of 15 participants (a) performed a series of maneuvers in an isolated parking lot, and (b) drove the vehicle in traffic along a defined ∼ 50 mile loop through the Seattle metropolitan area. We then ...

• Type: Journal
• Year: 2016
• Where: POPETS
• Authors: Miro Enev, Alex Takakuwa, Karl Koscher, Tadayoshi Kohno
• Keywords: POPETS 2016