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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CROW: Code Diversification for WebAssembly

Javier Cabrera Arteaga, Orestis Floros, Benoit Baudry, Martin Monperrus (KTH Royal Institute of Technology), Oscar Vera Perez (Univ Rennes, Inria, CNRS, IRISA)

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Bitcontracts: Supporting Smart Contracts in Legacy Blockchains

Karl Wüst (ETH Zurich), Loris Diana (ETH Zurich), Kari Kostiainen (ETH Zurich), Ghassan Karame (NEC Labs), Sinisa Matetic (ETH Zurich), Srdjan Capkun (ETH Zurich)

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IoTSafe: Enforcing Safety and Security Policy with Real IoT...

Wenbo Ding (Clemson University), Hongxin Hu (University at Buffalo), Long Cheng (Clemson University)

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Detecting DolphinAttacks Based on Microphone Array

Guoming Zhang, Xiaoyu Ji (Zhejiang University)

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