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A Non-Invasive Cyberrisk in Cooperative Driving

Bapp, Falco; Becker, J.; Beyerer, Jürgen; Doll, J.; Filsinger, M.; Frese, Ch; Hubschneider, Ch.; Lauber, A.; Müller-Quade, Jörn; Pauli, M.; Roschani, M.; Salscheider, Ole; Rosenhahn, B.; Ruf, M.; Stiller, Ch.; Willersinn, D.; Ziehn, J. R.


This paper presents a hacking risk arising in fullyautomated cooperative driving. As opposed to common cyberrisk scenarios, this scenario does not require internal access to an automated car at all, and is therefore largely independent of current on-board malware protection. A hacker uses a wireless mobile device, for example a hacked smartphone, to send vehicleto-vehicle (V2V) signals from a human-driven car, masquerading it as a fully-automated, cooperating vehicle. It deliberately engages only in high-risk cooperative maneuvers with other cars, in which the unwitting human driver is expected to perform a specific maneuver to avoid collisions with other vehicles. As the human driver is unaware of the planned maneuver, he fails to react as expected by the other vehicles; depending on the situation, a severe collision risk can ensue. We propose a vision-based countermeasure that only requires state-of-the-art equipment for fully-automated vehicles, and assures that such an attack without internal access to an automated car is impossible.

Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Institut für Hochfrequenztechnik und Elektronik (IHE)
Institut für Mess- und Regelungstechnik mit Maschinenlaboratorium (MRT)
Institut für Technik der Informationsverarbeitung (ITIV)
Institut für Theoretische Informatik (ITI)
Kompetenzzentrum für angewandte Sicherheitstechnologie (KASTEL)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2017
Sprache Englisch
Identifikator KITopen-ID: 1000078747
Erschienen in TÜV-Tagung Fahrerassistenz, 2017, München
Seiten 8 S.
Externe Relationen Abstract/Volltext
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