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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MIRROR: Model Inversion for Deep LearningNetwork with High Fidelity

Shengwei An (Purdue University), Guanhong Tao (Purdue University), Qiuling Xu (Purdue University), Yingqi Liu (Purdue University), Guangyu Shen (Purdue University); Yuan Yao (Nanjing University), Jingwei Xu (Nanjing University), Xiangyu Zhang (Purdue University)

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PMTUD is not Panacea: Revisiting IP Fragmentation Attacks against...

Xuewei Feng (Tsinghua University), Qi Li (Tsinghua University), Kun Sun (George Mason University), Ke Xu (Tsinghua University), Baojun Liu (Tsinghua University), Xiaofeng Zheng (Institute for Network Sciences and Cyberspace, Tsinghua University; QiAnXin Technology Research Institute & Legendsec Information Technology (Beijing) Inc.), Qiushi Yang (QiAnXin Technology Research Institute & Legendsec Information Technology (Beijing) Inc.), Haixin Duan…

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PoF: Proof-of-Following for Vehicle Platoons

Ziqi Xu (University of Arizona), Jingcheng Li (University of Arizona), Yanjun Pan (University of Arizona), Loukas Lazos (University of Arizona, Tucson), Ming Li (University of Arizona, Tucson), Nirnimesh Ghose (University of Nebraska–Lincoln)

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