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

Demystifying Local Business Search Poisoning for Illicit Drug Promotion

Peng Wang (Indiana University Bloomington), Zilong Lin (Indiana University Bloomington), Xiaojing Liao (Indiana University Bloomington), XiaoFeng Wang (Indiana University Bloomington)

Read More

Fine-Grained Coverage-Based Fuzzing

Bernard Nongpoh (Université Paris Saclay), Marwan Nour (Université Paris Saclay), Michaël Marcozzi (Université Paris Saclay), Sébastien Bardin (Université Paris Saclay)

Read More

GhostTalk: Interactive Attack on Smartphone Voice System Through Power...

Yuanda Wang (Michigan State University), Hanqing Guo (Michigan State University), Qiben Yan (Michigan State University)

Read More

Probe the Proto: Measuring Client-Side Prototype Pollution Vulnerabilities of...

Zifeng Kang (Johns Hopkins University), Song Li (Johns Hopkins University), Yinzhi Cao (Johns Hopkins University)

Read More