Cherin Lim, Tianhao Xu, Prashanth Rajivan (University of Washington)

Human trust is critical for the adoption and continued use of autonomous vehicles (AVs). Experiencing vehicle failures that stem from security threats to underlying technologies that enable autonomous driving, can significantly degrade drivers’ trust in AVs. It is crucial to understand and measure how security threats to AVs impact human trust. To this end, we conducted a driving simulator study with forty participants who underwent three drives including one that had simulated cybersecurity attacks. We hypothesize drivers’ trust in the vehicle is reflected through drivers’ body posture, foot movement, and engagement with vehicle controls during the drive. To test this hypothesis, we extracted body posture features from each frame in the video recordings, computed skeletal angles, and performed k-means clustering on these values to classify drivers’ foot positions. In this paper, we present an algorithmic pipeline for automatic analysis of body posture and objective measurement of trust that could be used for building AVs capable of trust calibration after security attack events.

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CAGE: Complementing Arm CCA with GPU Extensions

Chenxu Wang (Southern University of Science and Technology (SUSTech) and The Hong Kong Polytechnic University), Fengwei Zhang (Southern University of Science and Technology (SUSTech)), Yunjie Deng (Southern University of Science and Technology (SUSTech)), Kevin Leach (Vanderbilt University), Jiannong Cao (The Hong Kong Polytechnic University), Zhenyu Ning (Hunan University), Shoumeng Yan (Ant Group), Zhengyu He (Ant…

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Guess Which Car Type I Am Driving: Information Leak...

Dongyao Chen (Shanghai Jiao Tong University), Mert D. Pesé (Clemson University), Kang G. Shin (University of Michigan, Ann Arbor)

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Beyond the Bytes: Understanding the Limitations of Intrinsic Binary...

Peter Lafosse (Owner and Co-Founder of Vector 35 Inc.)

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DeGPT: Optimizing Decompiler Output with LLM

Peiwei Hu (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China), Ruigang Liang (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China), Kai Chen (Institute of Information Engineering, Chinese Academy of Sciences, China)

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