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)

Generating randomness by public participation allows participants to contribute randomness directly and verify the result's security. Ideally, the difficulty of participating in such activities should be as low as possible to reduce the computational burden of being a contributor. However, existing randomness generation protocols are unsuitable for this scenario because of scalability or usability issues. Hence, in this paper we present HeadStart, a participatory randomness protocol designed for public participation at scale. HeadStart allows contributors to verify the result on commodity devices efficiently, and provides a parameter $L$ that can make the result-publication latency $L$ times lower. Additionally, we propose two implementation improvements to speed up the verification further and reduce the proof size. The verification complexity of HeadStart is only $O(L times polylog(T) +log C)$ for a contribution phase lasting for time $T$ with $C$ contributions.

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Demo #4: Recovering Autonomous Robotic Vehicles from Physical Attacks

Pritam Dash (University of British Columbia) and Karthik Pattabiraman (University of British Columbia)

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Generating Test Suites for GPU Instruction Sets through Mutation...

Shoham Shitrit(University of Rochester) and Sreepathi Pai (University of Rochester)

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Demo #7: A Simulator for Cooperative and Automated Driving...

Mohammed Lamine Bouchouia (Telecom Paris - Institut Polytechnique de Paris), Jean-Philippe Monteuuis (Qualcomm Technologies Inc), Houda Labiod (Telecom Paris - Institut Polytechnique de Paris), Ons Jelassi (Telecom Paris - Institut Polytechnique de Paris), Wafa Ben Jaballah (Thales) and Jonathan Petit (Qualcomm Technologies Inc)

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DRAWN APART: A Device Identification Technique based on Remote...

Tomer Laor (Ben-Gurion Univ. of the Negev), Naif Mehanna and Antonin Durey (Univ. Lille / Inria), Vitaly Dyadyuk (Ben-Gurion Univ. of the Negev), Pierre Laperdrix (CNRS, Univ. Lille, Inria Lille), Clémentine Maurice (CNRS), Yossi Oren (Ben-Gurion Univ. of the Negev), Romain Rouvoy (Univ. Lille / Inria / IUF), Walter Rudametkin (Univ. Lille / Inria), Yuval…

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