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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Demo #3: I Am Not Afraid of the GPS...

Ali A. Abdallah (UC Irvine), Zaher M. Kassas (UC Irvine) and Chiawei Lee (US Air Force Test Pilot School)

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FakeGuard: Exploring Haptic Response to Mitigate the Vulnerability in...

Aditya Singh Rathore (University at Buffalo, SUNY), Yijie Shen (Zhejiang University), Chenhan Xu (University at Buffalo, SUNY), Jacob Snyderman (University at Buffalo, SUNY), Jinsong Han (Zhejiang University), Fan Zhang (Zhejiang University), Zhengxiong Li (University of Colorado Denver), Feng Lin (Zhejiang University), Wenyao Xu (University at Buffalo, SUNY), Kui Ren (Zhejiang University)

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RVPLAYER: Robotic Vehicle Forensics by Replay with What-if Reasoning

Hongjun Choi (Purdue University), Zhiyuan Cheng (Purdue University), Xiangyu Zhang (Purdue University)

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Model-Agnostic Defense for Lane Detection against Adversarial Attack

Henry Xu, An Ju, and David Wagner (UC Berkeley) Baidu Security Auto-Driving Security Award Winner ($1000 cash prize)!

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