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.

View More Papers

Fighting Fake News in Encrypted Messaging with the Fuzzy...

Linsheng Liu (George Washington University), Daniel S. Roche (United States Naval Academy), Austin Theriault (George Washington University), Arkady Yerukhimovich (George Washington University)

Read More

Drivers and Passengers Maybe the Weakest Link in the...

Aiping Xiong (Pennsylvania State University), Zekun Cai (Pennsylvania State University) and Tianhao Wang (University of Virginia)

Read More

CFInsight: A Comprehensive Metric for CFI Policies

Tommaso Frassetto (Technical University of Darmstadt), Patrick Jauernig (Technical University of Darmstadt), David Koisser (Technical University of Darmstadt), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

Read More

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

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

Read More