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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Ghada Dessouky (Technical University of Darmstadt), Emmanuel Stapf (Technical University of Darmstadt), Pouya Mahmoody (Technical University of Darmstadt), Alexander Gruler (Technical University of Darmstadt), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

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Ryan Tsang (University of California, Davis), Doreen Joseph (University of California, Davis), Qiushi Wu (University of California, Davis), Soheil Salehi (University of California, Davis), Nadir Carreon (University of Arizona), Prasant Mohapatra (University of California, Davis), Houman Homayoun (University of California, Davis)

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

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