Anas Alsoliman, Marco Levorato, and Qi Alfred Chen (UC Irvine)

In autonomous vehicle systems – whether ground or aerial – vehicles and infrastructure-level units communicate among each other continually to ensure safe and efficient autonomous operations. However, different attack scenarios might arise in such environments when a device in the network cannot physically pinpoint the actual transmitter of a certain message. For example, a compromised or a malicious vehicle could send a message with a fabricated location to appear as if it is in the location of another legitimate vehicle, or fabricate multiple messages with fake identities to alter the behavior of other vehicles/infrastructure units and cause traffic congestion or accidents. In this paper, we propose a Vision-Based Two-Factor Authentication and Localization Scheme for Autonomous Vehicles. The scheme leverages the vehicles’ light sources and cameras to establish an “Optical Camera Communication (OCC)” channel providing an auxiliary channel between vehicles to visually authenticate and localize the transmitter of messages that are sent over Radio Frequency (RF) channels. Additionally, we identify possible attacks against the proposed scheme as well as mitigation strategies.

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Polypyus – The Firmware Historian

Jan Friebertshauser, Florian Kosterhon, Jiska Classen, Matthias Hollick (Secure Mobile Networking Lab, TU Darmstad)

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More than a Fair Share: Network Data Remanence Attacks...

Leila Rashidi (University of Calgary), Daniel Kostecki (Northeastern University), Alexander James (University of Calgary), Anthony Peterson (Northeastern University), Majid Ghaderi (University of Calgary), Samuel Jero (MIT Lincoln Laboratory), Cristina Nita-Rotaru (Northeastern University), Hamed Okhravi (MIT Lincoln Laboratory), Reihaneh Safavi-Naini (University of Calgary)

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Emilia: Catching Iago in Legacy Code

Rongzhen Cui (University of Toronto), Lianying Zhao (Carleton University), David Lie (University of Toronto)

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