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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File Hijacking Vulnerability: The Elephant in the Room

Chendong Yu (Institute of Information Engineering, Chinese Academy of Sciences and School of Cyber Security, University of Chinese Academy of Sciences), Yang Xiao (Institute of Information Engineering, Chinese Academy of Sciences and School of Cyber Security, University of Chinese Academy of Sciences), Jie Lu (Institute of Computing Technology of the Chinese Academy of Sciences), Yuekang…

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Private Aggregate Queries to Untrusted Databases

Syed Mahbub Hafiz (University of California, Davis), Chitrabhanu Gupta (University of California, Davis), Warren Wnuck (University of California, Davis), Brijesh Vora (University of California, Davis), Chen-Nee Chuah (University of California, Davis)

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AdvCAPTCHA: Creating Usable and Secure Audio CAPTCHA with Adversarial...

Hao-Ping (Hank) Lee (Carnegie Mellon University), Wei-Lun Kao (National Taiwan University), Hung-Jui Wang (National Taiwan University), Ruei-Che Chang (University of Michigan), Yi-Hao Peng (Carnegie Mellon University), Fu-Yin Cherng (National Chung Cheng University), Shang-Tse Chen (National Taiwan University)

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Heterogeneous Graph Pre-training Based Model for Secure and Efficient...

Xurui Li (Fudan University), Xin Shan (Bank of Shanghai), Wenhao Yin (Shanghai Saic Finance Co., Ltd)

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