Noah T. Curran (University of Michigan), Kang G. Shin (University of Michigan), William Hass (Lear Corporation), Lars Wolleschensky (Lear Corporation), Rekha Singoria (Lear Corporation), Isaac Snellgrove (Lear Corporation), Ran Tao (Lear Corporation)

ETAS Best Short Paper Award Runner-Up!

On urban roadways, “dooring” remains a serious problem to the safety of pedestrians, cyclists, and other vulnerable road users (VRUs). Existing solutions that address this concern remain inadequate, as they either place unreasonable expectations on the pedestrians or rely on prohibitively expensive additions to the vehicle’s sensing capabilities. Consequently, typical consumer vehicles are not yet equipped with such a technology, and practical dooring prevention still remains a safety concern.
To address this problem, we propose a driver safety system for dooring prevention called S-Door that uses existing resources available in every modern vehicle: Bluetooth Low-Energy (BLE). Since a modern vehicle is distributively equipped with multiple BLE transceivers, we leverage each transceiver to observe BLE advertising data (AD) packets that consumers’ smart devices passively transmit. From these AD packets, we extract information that we can use to localize the VRU device without pairing with the device. With this information, we propose two methods for localization based on BLE versions ≤5.0 and ≥5.1, respectively. Our solutions are capable of alerting the driver of all instances of an oncoming VRU. Due to S-Door’s use of existing vehicle BLE hardware, we may extend this application to modern vehicles through a firmware update—no physical modification is necessary.

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Backdoor Attacks Against Dataset Distillation

Yugeng Liu (CISPA Helmholtz Center for Information Security), Zheng Li (CISPA Helmholtz Center for Information Security), Michael Backes (CISPA Helmholtz Center for Information Security), Yun Shen (Netapp), Yang Zhang (CISPA Helmholtz Center for Information Security)

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WIP: Savvy: Trustworthy Autonomous Vehicles Architecture

Ali Shoker, Rehana Yasmin, Paulo Esteves-Verissimo (Resilient Computing & Cybersecurity Center (RC3), KAUST)

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Fusion: Efficient and Secure Inference Resilient to Malicious Servers

Caiqin Dong (Jinan University), Jian Weng (Jinan University), Jia-Nan Liu (Jinan University), Yue Zhang (Jinan University), Yao Tong (Guangzhou Fongwell Data Limited Company), Anjia Yang (Jinan University), Yudan Cheng (Jinan University), Shun Hu (Jinan University)

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