Mulong Luo (Cornell University) and G. Edward Suh (Cornell University)

Effective coordination of sensor inputs requires correct timestamping of the sensor data for robotic vehicles. Though the existing trusted execution environment (TEE) can prevent direct changes to timestamp values from a clock or while stored in memory by an adversary, timestamp integrity can still be compromised by an interrupt between sensor and timestamp reads. We analytically and experimentally evaluate how timestamp integrity violations affect localization of robotic vehicles. The results indicate that the interrupt attack can cause significant errors in localization, which threatens vehicle safety, and need to be prevented with additional countermeasures.

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What You See is Not What the Network Infers:...

Yijun Yang (The Chinese University of Hong Kong), Ruiyuan Gao (The Chinese University of Hong Kong), Yu Li (The Chinese University of Hong Kong), Qiuxia Lai (Communication University of China), Qiang Xu (The Chinese University of Hong Kong)

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PASS: A System-Driven Evaluation Platform for Autonomous Driving Safety...

Zhisheng Hu (Baidu Security), Junjie Shen (UC Irvine), Shengjian Guo (Baidu Security), Xinyang Zhang (Baidu Security), Zhenyu Zhong (Baidu Security), Qi Alfred Chen (UC Irvine) and Kang Li (Baidu Security)

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Forensic Analysis of Configuration-based Attacks

Muhammad Adil Inam (University of Illinois at Urbana-Champaign), Wajih Ul Hassan (University of Illinois at Urbana-Champaign), Ali Ahad (University of Virginia), Adam Bates (University of Illinois at Urbana-Champaign), Rashid Tahir (University of Prince Mugrin), Tianyin Xu (University of Illinois at Urbana-Champaign), Fareed Zaffar (LUMS)

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ROV-MI: Large-Scale, Accurate and Efficient Measurement of ROV Deployment

Wenqi Chen (Tsinghua University), Zhiliang Wang (Tsinghua University), Dongqi Han (Tsinghua University), Chenxin Duan (Tsinghua University), Xia Yin (Tsinghua University), Jiahai Yang (Tsinghua University), Xingang Shi (Tsinghua University)

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