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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EMS: History-Driven Mutation for Coverage-based Fuzzing

Chenyang Lyu (Zhejiang University), Shouling Ji (Zhejiang University), Xuhong Zhang (Zhejiang University & Zhejiang University NGICS Platform), Hong Liang (Zhejiang University), Binbin Zhao (Georgia Institute of Technology), Kangjie Lu (University of Minnesota), Raheem Beyah (Georgia Institute of Technology)

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HeadStart: Efficiently Verifiable and Low-Latency Participatory Randomness Generation at...

Hsun Lee (National Taiwan University), Yuming Hsu (National Taiwan University), Jing-Jie Wang (National Taiwan University), Hao Cheng Yang (National Taiwan University), Yu-Heng Chen (National Taiwan University), Yih-Chun Hu (University of Illinois at Urbana-Champaign), Hsu-Chun Hsiao (National Taiwan University)

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Local and Central Differential Privacy for Robustness and Privacy...

Mohammad Naseri (University College London), Jamie Hayes (DeepMind), Emiliano De Cristofaro (University College London & Alan Turing Institute)

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Transparency Dictionaries with Succinct Proofs of Correct Operation

Ioanna Tzialla (New York University), Abhiram Kothapalli (Carnegie Mellon University), Bryan Parno (Carnegie Mellon University), Srinath Setty (Microsoft Research)

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