Wentao Chen, Sam Der, Yunpeng Luo, Fayzah Alshammari, Qi Alfred Chen (University of California, Irvine)

Due to the cyber-physical nature of robotic vehicles, security is especially crucial, as a compromised system not only exposes privacy and information leakage risks, but also increases the risk of harm in the physical world. As such, in this paper, we explore the current vulnerability landscape of robotic vehicles exposed to and thus remotely accessible by any party on the public Internet. Focusing particularly on instances of the Robot Operating System (ROS), a commonly used open-source robotic software framework, we performed new Internet-wide scans of the entire IPv4 address space, identifying, categorizing, and analyzing the ROS-based systems we discovered. We further performed the first measurement of ROS scanners in the wild by setting up ROS honeypots, logging traffic, and analyzing the traffic we received. We found over 190 ROS systems on average being regularly exposed to the public Internet and discovered new trends in the exposure of different types of robotic vehicles, suggesting increasing concern regarding the cybersecurity of today’s ROS-based robotic vehicle systems.

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WIP: Practical Removal Attacks on LiDAR-based Object Detection in...

Takami Sato (University of California, Irvine), Yuki Hayakawa (Keio University), Ryo Suzuki (Keio University), Yohsuke Shiiki (Keio University), Kentaro Yoshioka (Keio University), Qi Alfred Chen (University of California, Irvine)

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Beyond the Surface: Uncovering the Unprotected Components of Android...

Hao Zhou (The Hong Kong Polytechnic University), Shuohan Wu (The Hong Kong Polytechnic University), Chenxiong Qian (University of Hong Kong), Xiapu Luo (The Hong Kong Polytechnic University), Haipeng Cai (Washington State University), Chao Zhang (Tsinghua University)

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It’s Standards’ Time to Shine: Insights for IoT Cybersecurity...

Dr. Michael J. Fagan, National Institute of Standards and Technology

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EM Eye: Characterizing Electromagnetic Side-channel Eavesdropping on Embedded Cameras

Yan Long (University of Michigan), Qinhong Jiang (Zhejiang University), Chen Yan (Zhejiang University), Tobias Alam (University of Michigan), Xiaoyu Ji (Zhejiang University), Wenyuan Xu (Zhejiang University), Kevin Fu (Northeastern University)

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