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.

View More Papers

Hunting the Haunter — Efficient Relational Symbolic Execution for...

Lesly-Ann Daniel (CEA, List, France), Sébastien Bardin (CEA, List, France), Tamara Rezk (Inria, France)

Read More

PrivacyFlash Pro: Automating Privacy Policy Generation for Mobile Apps

Sebastian Zimmeck (Wesleyan University), Rafael Goldstein (Wesleyan University), David Baraka (Wesleyan University)

Read More

Demo #2: Sequential Attacks on Kalman Filter-Based Forward Collision...

Yuzhe Ma, Jon Sharp, Ruizhe Wang, Earlence Fernandes, and Jerry Zhu (University of Wisconsin–Madison)

Read More

Work in Progress: Programmable In-Network Obfuscation of DNS Traffic

Liang Wang, Hyojoon Kim, Prateek Mittal, Jennifer Rexford (Princeton University)

Read More