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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Data Poisoning Attacks to Deep Learning Based Recommender Systems

Hai Huang (Tsinghua University), Jiaming Mu (Tsinghua University), Neil Zhenqiang Gong (Duke University), Qi Li (Tsinghua University), Bin Liu (West Virginia University), Mingwei Xu (Tsinghua University)

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Reining in the Web's Inconsistencies with Site Policy

Stefano Calzavara (Università Ca' Foscari Venezia), Tobias Urban (Institute for Internet Security and Ruhr University Bochum), Dennis Tatang (Ruhr University Bochum), Marius Steffens (CISPA Helmholtz Center for Information Security), Ben Stock (CISPA Helmholtz Center for Information Security)

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Preventing and Detecting State Inference Attacks on Android

Andrea Possemato (IDEMIA and EURECOM), Dario Nisi (EURECOM), Yanick Fratantonio (EURECOM and Cisco Talos)

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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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