Ningfei Wang (University of California, Irvine), Shaoyuan Xie (University of California, Irvine), Takami Sato (University of California, Irvine), Yunpeng Luo (University of California, Irvine), Kaidi Xu (Drexel University), Qi Alfred Chen (University of California, Irvine)

Traffic Sign Recognition (TSR) is crucial for safe and correct driving automation. Recent works revealed a general vulnerability of TSR models to physical-world adversarial attacks, which can be low-cost, highly deployable, and capable of causing severe attack effects such as hiding a critical traffic sign or spoofing a fake one. However, so far existing works generally only considered evaluating the attack effects on academic TSR models, leaving the impacts of such attacks on real-world commercial TSR systems largely unclear. In this paper, we conduct the first large-scale measurement of physical-world adversarial attacks against commercial TSR systems. Our testing results reveal that it is possible for existing attack works from academia to have highly reliable (100%) attack success against certain commercial TSR system functionality, but such attack capabilities are not generalizable, leading to much lower-than-expected attack success rates overall. We find that one potential major factor is a spatial memorization design that commonly exists in today's commercial TSR systems. We design new attack success metrics that can mathematically model the impacts of such design on the TSR system-level attack success, and use them to revisit existing attacks. Through these efforts, we uncover 7 novel observations, some of which directly challenge the observations or claims in prior works due to the introduction of the new metrics.

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Zihan Qu (Johns Hopkins University), Xinyi Qu (University College London), Xin Shen, Zhen Liang, and Jianjia Yu (Johns Hopkins University)

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HADES Attack: Understanding and Evaluating Manipulation Risks of Email...

Ruixuan Li (Tsinghua University), Chaoyi Lu (Tsinghua University), Baojun Liu (Tsinghua University;Zhongguancun Laboratory), Yunyi Zhang (Tsinghua University), Geng Hong (Fudan University), Haixin Duan (Tsinghua University;Zhongguancun Laboratory), Yanzhong Lin (Coremail Technology Co. Ltd), Qingfeng Pan (Coremail Technology Co. Ltd), Min Yang (Fudan University), Jun Shao (Zhejiang Gongshang University)

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Spatial-Domain Wireless Jamming with Reconfigurable Intelligent Surfaces

Philipp Mackensen (Ruhr University Bochum), Paul Staat (Max Planck Institute for Security and Privacy), Stefan Roth (Ruhr University Bochum), Aydin Sezgin (Ruhr University Bochum), Christof Paar (Max Planck Institute for Security and Privacy), Veelasha Moonsamy (Ruhr University Bochum)

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Anqi Tian (Institute of Software, Chinese Academy of Sciences; School of Computer Science and Technology, University of Chinese Academy of Sciences), Peifang Ni (Institute of Software, Chinese Academy of Sciences; Zhongguancun Laboratory, Beijing, P.R.China), Yingzi Gao (Institute of Software, Chinese Academy of Sciences; University of Chinese Academy of Sciences), Jing Xu (Institute of Software, Chinese…

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