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

Kalman Filter (KF) is widely used in various domains to perform sequential learning or variable estimation. In the context of autonomous vehicles, KF constitutes the core component of many Advanced Driver Assistance Systems (ADAS), such as Forward Collision Warning (FCW). It tracks the states (distance, velocity etc.) of relevant traffic objects based on sensor measurements. The tracking output of KF is often fed into downstream logic to produce alerts, which will then be used by human drivers to make driving decisions in near-collision scenarios. In this work, we demonstrate planning-based attacks on Forward Collision Warning — a machine-human hybrid system that uses KF. Based on our work published at the AAAI2021 conference, we use an MPC-based algorithm and show how an attacker can sequentially perturb vision measurements to change the FCW alert signals at desired points in time. We simulate our attack on CARLA using standard test protocols from the National Highway Traffic Safety Administration.

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Cross-National Study on Phishing Resilience

Shakthidhar Reddy Gopavaram (Indiana University), Jayati Dev (Indiana University), Marthie Grobler (CSIRO’s Data61), DongInn Kim (Indiana University), Sanchari Das (University of Denver), L. Jean Camp (Indiana University)

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V2X Security: Status and Open Challenges

Jonathan Petit (Director Of Engineering at Qualcomm Technologies) Dr. Jonathan Petit is Director of Engineering at Qualcomm Technologies, Inc., where he leads research in security of connected and automated vehicles (CAV). His team works on designing security solutions, but also develops tools for automotive penetration testing and builds prototypes. His recent work on misbehavior protection…

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The Nuts and Bolts of Building FlowLens

Diogo Barradas (Instituto Superior Técnico, Universidade de Lisboa)

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A Formal Analysis of the FIDO UAF Protocol

Haonan Feng (Beijing University of Posts and Telecommunications), Hui Li (Beijing University of Posts and Telecommunications), Xuesong Pan (Beijing University of Posts and Telecommunications), Ziming Zhao (University at Buffalo)

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